Landscape Ecology in Agroecosystems Management (Advances in Agroecology)

LANDSCAPE ECOLOGY in AGROECOSYSTEMS MANAGEMENT

Advances in Agroecology Series Editor: Clive A. Edwards Soil Ecology in Sustainable Agricultural Systems, Lijbert Brussaard and Ronald Ferrera-Cerrato Biodiversity in Agroecosystems, Wanda Williams Collins and Calvin O. Qualset Agroforestry in Sustainable Agricultural Systems, Louise E. Buck, James P. Lassoie, and Erick C.M. Fernandes Agroecosystem Sustainability: Developing Practical Strategies, Stephen R. Gliessman Interactions Between Agroecosystems and Rural Communities Cornelia Flora Structure and Function in Agroecosystem Design and Management Masae Shiyomi and Hiroshi Koizumi

Advisory Board Editor-in-Chief Clive A. Edwards The Ohio State University, Columbus, OH Editorial Board Miguel Altieri University of California, Berkeley, CA Lijbert Brussaard Agricultural University, Wageningen, The Netherlands David Coleman University of Georgia, Athens, GA D.A. Crossley, Jr. University of Georgia, Athens, GA Adel El-Titi Stuttgart, Germany Charles A. Francis University of Nebraska, Lincoln, NE Stephen R. Gliessman University of California, Santa Cruz Thurman Grove North Carolina State University, Raleigh, NC Maurizio Paoletti University of Padova, Padova, Italy David Pimentel Cornell University, Ithaca, NY Masae Shiyomi Ibaraki University, Mito, Japan Sir Colin R.W. Spedding Berkshire, England Moham K. Wali The Ohio State University, Columbus, OH

LANDSCAPE ECOLOGY in AGROECOSYSTEMS MANAGEMENT Edited by

Lech Ryszkowski

CRC PR E S S Boca Raton London New York Washington, D.C.

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Cover Art Top: Example of damage resulting from erosion and pollution in a beet field in Erlon, northern Parisian basin. (From F. Tellier, June 1999.) Bottom: Shaded composition of General Chlapowski ’s Agro-ecological Park (Greater Poland), Satellite Image SPOT HRV-17, June 1997.

Library of Congress Cataloging-in-Publication Data Landscape ecology in agroecosystems management / edited by Lech Ryszkowski. p. cm. -- (Advances in agroecology) Includes bibliographical references (p. ). ISBN 0-8493-0919-0 (alk. paper) 1. Landscape ecology. 2. Agricultural ecology. 3. Ecosystem management. I. Ryszkowski, Lech. II. Series. QH541.15.L35 L347 2001 577.5′5--dc21

2001052416

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Visit the CRC Press Web site at www.crcpress.com © 2002 by CRC Press LLC No claim to original U.S. Government works International Standard Book Number 0-8493-0919-0 Library of Congress Card Number 2001052416 Printed in the United States of America 1 2 3 4 5 6 7 8 9 0 Printed on acid-free paper

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The Editor Lech Ryszkowski, Ph.D., is Professor of Natural Sciences and Director of the Research Centre for Agricultural and Forest Environment of the Polish Academy of Sciences in Poznan´ , Poland. He graduated from the Faculty of Biology and Earth Sciences in 1955 and completed his Ph.D. on coypu population structure in 1963. In 1971, he received his Doctor of Sciences from Warsaw University for his studies on the role of small mammal communities in energy flows of temperate forest ecosystems. For 2 years, he was the student of Eugene Odum at the University of Georgia in Athens. Dr. Ryszkowski became an Associate Professor in 1971 and a Full Professor nominated by the State Council in 1985. Dr. Ryszkowski’s major interests are the functional role of animals in agroecosystem energy flow and matter cycling, and energy flow and matter cycling at the level of agricultural landscape with emphasis on the role of ecotones (e.g., mid-field shelterbelts or stretches of meadows) in control of elements cycling in rural areas. His main scientific achievements focus on guidelines for the protection of rural environment and for the biological conservation and management of agricultural landscapes. Particular emphasis is placed on the possibilities of control over nonpoint pollution sources by the formation of biogeochemical barriers such as woodlots shelterbelts, grasslands, and water bodies differentiating agricultural landscape. Dr. Ryszkowski is the head of the International Group for Agroecosystems and a member of many ecological organizations. He was a member of the Board of INTECOL (1992 to 1998) and has organized many international symposia. As a member of the Countryside, Wildlife and Landscape Working Group of the Council of Europe in Strasbourg, Dr. Ryszkowski presented two reports on landscape and biological diversity in the Central and Eastern European countries and was the Polish organizer of the symposium on landscape diversity in rural areas for the Council of Europe. Dr. Ryszkowski has published 354 papers in Polish and international journals. He is the editor or co-editor of 18 books.

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Contributors Ewa Arczynska-Chudy Research Centre for Agricultural and Forest Environment Pozna n´ , Poland Stanislaw Ba l azy Research Centre for Agricultural and Forest Environment Pozna n´ , Poland Gary W. Barrett Institute of Ecology University of Georgia Athens, Georgia, U.S.A. Alina Bartoszewicz Department of Soil Science Agricultural University Pozna n´ , Poland Jacques Baudry INRA Rennes, France Françoise Burel Laboratoire d’Evolution des Systemes Naturels et Modifiés Université de Rennes I Campus de Beaulieu Rennes, France Susan R. Crow Carl Vinson Institute of Government and College of Agricultural and Environmental Sciences University of Georgia Tifton, Georgia, U.S.A. Frank Eulenstein Institute of Land Use Systems and Landscape Ecology Center for Agricultural Landscape and Land Use Research Müncheberg, Germany

Marc Galochet Center of Biogeography-Ecology (UMR 8505-CNRS/ENS) Saint-Cloud, France and University of Paris IV — Sorbonne Paris, France Bärbel Gerowitt Georg-August-Universität Landwirtschaft und Umwelt Göttingen, Germany Vincent Godard Center of Biogeography-Ecology (UMR 8505-CNRS/ENS) Saint-Cloud, France and University of Paris VIII — Saint-Denis Saint-Denis, France Hanna Go l dyn Research Centre for Agricultural and Forest Environment Pozna n´ , Poland Micheline Hotyat Center of Biogeography-Ecology (UMR 8505-CNRS/ENS) Saint-Cloud, France and University of Paris IV — Sorbonne Paris, France Janusz Jankowiak Research Centre for Agricultural and Forest Environment Pozna n´ , Poland Wonter Joenje Department of Plant Science Agricultural University Wageningen Wageningen, the Netherlands

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Jerzy Karg Research Centre for Agricultural and Forest Environment Pozna n´ , Poland

Jon Marshall Marshall Agroecology Barton, Winscombe Somerset, U.K.

Andrzej Ke˛ dziora Department of Agrometeorology Agricultural University im A. Cieszkowskiego Pozna n´ , Poland and Research Centre for Agricultural and Forest Environment Pozna n´ , Poland

Andrzej Mizgajski Educational Center for Environment Protection and Sustainable Development A. Mickiewicz University Pozna n´ , Poland

David Kleijn Department of Environmental Sciences Nature Conservation and Plant Ecology Group Wageningen University Bornsesteeg, Wageningen The Netherlands Krzysztof Kujawa Research Centre for Agricultural and Forest Environment Pozna n´ , Poland Didier Le Coeur Laboratoire d’Ecologie et Sciences Phytosanitaires Ecole Nationale Superieure Agronomique de Rennes Rennes, France Richard Lowrance Southeast Watershed Research Laboratory Agricultural Research Service United States Department of Agriculture Tifton, Georgia, U.S.A.

Camilla Moonen Scuola Superiore Santa Anna Pisa, Italy Janusz Olejnik Department of Agrometeorology Agricultural University im A. Cieszkowskiego Pozna n´ , Poland and Department of Land Use Systems and Landscape Ecology Center for Agricultural Landscape and Land Use Research (ZALF) Müncheberg, Germany Maurizio Paoletti Dipatimento di Biologia Università Degli Studi di Padova Padova, Italy Lech Ryszkowski Research Centre for Agricultural and Forest Environment Pozna n´ , Poland Laura E. Skelton Institute of Ecology University of Georgia Athens, Georgia, U.S.A.

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Lech Szajdak Research Centre for Agricultural and Forest Environment Pozna n´ , Poland Barbara Szpakowska Research Centre for Agricultural and Forest Environment Pozna n´ , Poland George Thomas Department of Agriculture and Food Studies Seale-Hayne Faculty University of Plymouth Newton Abbot, Devon, U.K. Armin Werner Department of Land Use Systems and Landscape Ecology Center for Agricultural Landscape and Land Use Research (ZALF) Müncheberg, Germany

Stanislas Wicherek Center of Biogeography-Ecology (UMR 8505 CNRS/ENS) Saint-Cloud, France and Member, Board of Directors and Vice-Chairman European Institute of Sustainable Development http://www.iedd.org-www.iedd.net Peter Zander Department of Socioeconomics and Department of Land Use Systems and Landscape Ecology Center for Agricultural Landscape and Land Use Research (ZALF) Müncheberg, Germany Irena Zyczynska-Baloniak Research Centre for Agricultural and Forest Environment Pozna n´ , Poland

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Contents Chapter 1 The Functional Approach to Agricultural Landscape Analysis................................1 Lech Ryszkowski Chapter 2 Development of Agriculture and Its Impact on Landscape Functions.....................9 Lech Ryszkowski and Janusz Jankowiak Chapter 3 Mitigation of Radiation and Heat Balance Structure by Plant Cover Structure....29 Janusz Olejnik, Andrzej Ke˛ dziora, and Frank Eulenstein Chapter 4 Water Balance in Agricultural Landscape and Options for Its Management by Change in Plant Cover Structure of Landscape ................................................57 Andrzej Ke˛ dziora, Janusz Olejnik, and Frank Eulenstein Chapter 5 Control of Diffuse Pollution by Mid-Field Shelterbelts and Meadow Strips ......111 Lech Ryszkowski, Lech Szajdak, Alina Bartoszewicz, · and Irena Zyczyn´ ska-Ba l oniak Chapter 6 Implementation of Riparian Buffer Systems for Landscape Management ..........145 Richard Lowrance and Susan R. Crow Chapter 7 Dissolved Organic Substances in Water Bodies of Agricultural Landscapes ......159 Barbara Szpakowska Chapter 8 Influence of Landscape Mosaic Structures on Diversity of Wild Plant and Animal Communities in Agricultural Landscapes of Poland ........................185 Lech Ryszkowski, Jerzy Karg, Krzysztof Kujawa, Hanna Go l dyn, and Ewa Arczyn´ ska-Chudy Chapter 9 Field Boundary Habitats for Wildlife, Crop, and Environmental Protection.......219 Jon Marshall, Jacques Baudry, Françoise Burel, Wouter Joenje, Bärbel Gerowitt, Maurizio Paoletti, George Thomas, David Kleijn, Didier Le Coeur, and Camilla Moonen

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Chapter 10 Changes in Landscape Diversity Patterns in the Province of Wielkopolska, Poland, Influenced by Agriculture.........................................................................249 Andrzej Mizgajski Chapter 11 The Impact of Agriculture on the Environment of the Northern Parisian Basin ..............................................................................263 Stanislas Wicherek Chapter 12 Models Assessing the Impact of Land-Use Change in Rural Areas on Development of Environmental Threats and Their Use for Agricultural Politics .........................................................................................277 Armin Werner and Peter Zander Chapter 13 Ecological Guidelines for the Management of Afforestations in Rural Areas ....299 Stanis l aw Ba l azy Chapter 14 Land Units and the Biodiversity of Forest Islets: From Satellite Images to Ground Analysis................................................................................................317 Marc Galochet, Vincent Godard, and Micheline Hotyat Chapter 15 Agrolandscape Ecology in the 21st Century ........................................................331 Gary W. Barrett and Laura E. Skelton Chapter 16 Agriculture and Landscape Ecology .....................................................................341 Lech Ryszkowski Index ......................................................................................................................349

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CHAPTER

1

The Functional Approach to Agricultural Landscape Analysis Lech Ryszkowski

CONTENTS Overview....................................................................................................................1 Emergence of the Discipline .....................................................................................2 Scale of Landscape Ecology .....................................................................................2 Feedback Mechanisms...............................................................................................3 Options Explored in This Book ................................................................................4 Outlook ......................................................................................................................6 References..................................................................................................................7

OVERVIEW In response to a growing need to bridge aspects of geography and ecology, Troll (1950, 1968) coined the term “landscape ecology,” which was adopted as a new scientific discipline. According to Troll (1968), the landscape can be studied in terms of its morphology, classification, and changes in time (history), as well as the functional relationships between its components, which he called landscape ecology. Troll also considered that problems of landscape protection as well as management should be included in geographical analyses of landscapes. Although these fields of landscape study are closely interrelated, the first three depend on a geographical approach, whereas the second two are ecological. In the 1950s, when Troll first introduced the term landscape ecology, the main concerns of ecology were focused on interrelations between organisms and their organic environment and on interactions between organisms. Studies of energy flows, organic matter cycling, and their control mechanisms, which were developing at that time, were especially stimulated

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by the International Biological Programme in the late 1960s and the first half of the 1970s. These studies broadened the functional analysis of ecosystems or landscapes, thereby providing insights into driving forces for dynamic processes (energy fluxes causing the transformation of structures) and also introduced new options for the control of environmental threats brought about by the intensification of agriculture and other human impacts on ecosystems. Other studies published at the same times as Troll’s papers also stressed the importance of an ecological approach to landscape analysis, especially for problems of landscape management. For example, Wodziczko (1948) in Poland strongly emphasized that the maintenance of biological balance in landscapes was an essential goal of protection or restoration activities. Wodziczko also introduced the term physiotactics for the ecological management of landscapes, which in 1953 Odum called ecological engineering.

EMERGENCE OF THE DISCIPLINE The progressive interest in landscape studies eventually resulted in the emergence of landscape ecology as a separate scientific discipline incorporating both geographical and ecological studies with landscape planning and management aspects. By the 1980s, landscape ecology was an established discipline, marked by the organization of the International Association for Landscape Ecology (IALE) in 1982 and the publication of books summarizing its scope and goals. Benchmark publications include those of Naveh and Lieberman (1984) and Forman and Godron (1986). Naveh and Lieberman stressed the role of human impact on landscape structures and functions and proposed ways for restoring degraded landscapes. Thus, their appreciation of landscapes reflected the approach of both the landscape designer and the environment protectionist as well as the social geographer. Forman and Godron emphasized the ecological aspects of landscape function. One very interesting result of their functional analysis was the proposition of the landscape stability principle, which indicates the importance of landscape structural heterogeneity in developing resistance to disturbances, recovery from disturbances, and total system stability. This principle was an outstanding contribution to general ecological theories identifying the importance of relationships among the various components of the landscape in maintaining resistance to external threats.

SCALE OF LANDSCAPE ECOLOGY The geographical approach reflected in analyses of land-use changes (e.g., Turner et al. 1990, Brouwer et al. 1991), which has always played an important role in landscape ecology studies, is clearly seen in the programs of consecutive IALE conferences. Thus, the field of landscape ecology is as heterogeneous as are the subjects of its studies. Recognition of this situation leads to acceptance of multifunctional properties of landscapes. Physical, chemical, and biological processes

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forming the natural basis for landscape function are interwoven with the economic, social, cultural, and political spheres of human activities. As a result of such interactions, the landscape structure may be changed in ways that in turn influence landscape functions. The interactions between natural and human-induced processes are fundamental to understanding conflicts between ecological and human systems (Haines-Young and Potschin 2000). The scale of landscapes, and to a lesser extent ecosystems, is such that changes in their component structure have implications for modifications or resistance to threats to their function by human activities. Therefore, the landscape constitutes a suitable ecological unit for management of environmental threats as well as a functional unit that can reflect interactions of ecological and human aspects of processes. A comprehensive analysis of a landscape enables not only the identification of ecological and human-induced processes in a holistic way but also may help detect the sources of threats to the sustainable development of agriculture or other human activities. The optimization of human activities directed toward specific goals in coordination with properties of natural systems is a fundamental assumption of successful environmental protection. As Haines-Young and Potschin (2000) articulated this question, the ecological services or resources are exploited according to their values to society, and such values observed by society cannot be resolved unless their relations to ecological functions are understood. A complete understanding of these natural relationships should also include the historical aspect, which is how human values are redefined in terms of ecological functional knowledge. In this context, human needs should be accommodated to ecological processes rather than subjugated to them.

FEEDBACK MECHANISMS The recognition of feedback mechanisms between the functions of landscapes and the exploitation of goods or services needed by human society should form a first step in developing strategies for sustainable development of the countryside. In many situations, deterioration of the environment caused by human activities was observed, but the causal relationships underpinning such phenomena were often poorly recognized. As a result, there was a widespread belief that human economic activities cannot be coordinated with protection of nature. However, with increasing recognition of a landscape’s basic processes, such as energy fluxes, organic matter cycling, and mechanisms of their management, there is a growing conviction that it is the way in which natural resources are used, not the fact that they are exploited, that has led to environmental degradation (Ryszkowski 2000). The argument that the less an ecosystem or landscape is changed by human activities, the less it is degraded, is challenged by the proposition that people using knowledge of landscape functions can enhance or substitute controlling negative feedbacks loops between natural and human-induced processes to such an extent that sustainable systems could be developed. Such an approach facilitates a more objective

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evaluation of alternative technologies of production, with objectives that seek to optimize production and environmental protection and to meet social needs at the same time. It cannot be stressed enough that this goal cannot be achieved on a scale smaller than the landscape, and that landscape ecology therefore becomes a very important pillar for the implementation of sustainable development of agriculture.

OPTIONS EXPLORED IN THIS BOOK The results of various studies presented in the subsequent chapters of this book further document this idea. Some of the results, described more fully in the various chapters, are provided here to highlight the options for the management of threats to the environment and enable development of guidelines for the implementation of an environmentally friendly landscape management. The successful management of agricultural landscapes depends on a full recognition of the relationships between those processes and structures that maintain the whole system. Concerns are often focused on simplified input and output analyses that consider the reacting system as a black box. This approach does not allow for any modification of environmental threats by rearrangement of system components, which could increase inner compensation processes that can amend unwanted effects. Chapter 2, relying on long-term interdisciplinary studies on agricultural landscapes carried out by the Research Centre for Agricultural and Forest Environment in Pozna n´ , Poland as well as on a vast quantity of literature, evaluates the functional changes of agroecosystems compared to natural ecosystems. Because of structural simplifications in agroecosystems, brought about by the obvious need to increase yields, the cultivated fields are characterized by a lower tie-up of organic matter cycling, which can result in increased leaching or wind loss of chemicals from cultivated fields. Farmers can moderate the intensity of various material-dispersing processes through properly applied tillage technologies, but they are unable to eliminate them entirely regardless of whether they use integrated or organic farming systems. Combining on-farm environmentally friendly technologies with the structuring of associated landscapes with various stretches of permanent vegetation can provide a more successful elimination of environmental threats. Thus, protection activities carried out at the landscape level can enhance environmentally friendly technologies applied within the farm. The functions that are of the utmost significance for landscape management, such as partition of solar energy for evapotranspiration and air and soil heating, are rarely considered in landscape studies. The newer methods of heat balance estimates under field conditions, relying on empirical relationships between solar energy fluxes and meteorological characteristics described by Ke˛ dziora and co-workers (see Chapters 3 and 4), have opened new frontiers for the management of water cycling and the conditioning of cultivated field microclimatic characteristics. The studies show clearly that manipulation of the plant cover structure of a landscape can change evapotranspiration rates and thus influence water cycling in the region. Manipulations with plant cover structure can also influence air heating, which, through

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convection processes, can modify mesoscale atmospheric circulation, which in turn influences regional climatic phenomena. The other important function of landscape studies is the control of diffuse aspects of water pollution caused by leaching of chemical compounds from the soil of cultivated fields. Information presented in Chapter 5 provides new insights on control mechanisms of diffuse pollution operating in permanent vegetation strips (biogeochemical barriers) located in agricultural landscapes. Thus, for example, biological recycling of nitrogen within the biogeochemical barrier plays a very important role in the efficiency of its retention. When rates of organic matter decomposition overcome the rates of nitrogen uptake by organisms, the biogeochemical barrier changes from a sink to a source of nitrogen pollution in the water reservoirs of a landscape. Thus, management of biogeochemical barriers is essential if their waterpurifying functions are to be retained. The indication that shelterbelts located in upland parts of watersheds can slow rates of nitrous oxide release to the atmosphere, compared to that occurring in adjoining cultivated fields, is an another example that the disclosure of the inner mechanisms operating in the biogeochemical barriers can provide options for the management of organic matter cycles at the landscape level. The implementation of agricultural landscape management for optimization of biomass production with environmental protection should be stimulated by a policy encouraging farmers to undertake certain actions. Chapter 6 discusses U.S. policies for the implementation of riparian buffer strips as a means of diffuse pollution control, emphasizing both the achievements and the obstacles. Chapter 7 examines studies concerning waterborne transport of organic compounds in the ground water under the agricultural landscape and provides an almost pioneering analysis of factors influencing those processes. The formation of metalorganic complexes, the influence of the biogeochemical barrier on processes of chemical speciation, which causes change in the ionic forms of chemical compounds, shows that water transport of chemicals is a very complicated phenomenon. Solubility, hence the toxicity to organisms of mineral compounds, could be changed enormously when the relevant inorganic ions are bound to organic compounds, which usually occurs when ground water seeps through the root system of the biogeochemical barrier. Consequently, for effective control of waterborne migration of heavy metals through a landscape, it is necessary to recognize the chemical forms of their transport. Chapters 8 and 9 report on studies showing that semi-natural habitats, maintained in the agricultural landscape, can constitute important refuge for many plants and animals, thereby supporting biological diversity in farmland. Thus, the introduction of a mosaic landscape, composed of cultivated fields and semi-natural habitats, to some extent compensates for the negative effects exerted by agriculture on the biota. The effects of stimulating biodiversity can appear very quickly when a new shelterbelt is planted, and in 2 to 3 years a very high level of biodiversity is achieved (Chapter 8). Farming operations have an influence on semi-natural habitats, and the various measures proposed in Chapter 9 for their protection can enhance protection of biodiversity. The results of the studies reported in Chapter 9 were obtained from a project executed in five European countries, so these conclusions have wide applicability.

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Agriculture-induced changes in environment are discussed in Chapters 10 and 11. Comparison of results presented in Chapters 10 and 11 shows some common threats for both regions discussed (the Wielkopolska and the Northern Parisian Basin), such as erosion processes or ground water pollution, which were created by the intensification of agriculture. The different climatic conditions of the regions produced different threats related to induced changes in water cycling. In the Wielkopolska, because of relatively low precipitation and high evapotranspiration, the drainage of cultivated fields resulted in an overall drying of the region (Chapter 10). In France, rapid removal of water from cultivated fields under moist Atlantic climatic conditions resulted in an increase in the severity of floods (Chapter 11). These areas illustrate clearly that the effects of introduced agricultural technology (drainage) can lead to different environmental effects if the regimes of matter cycling (water) in the whole system are different. Chapter 12 shows the methods of forecasting threats that can be induced by various trends in changes in agricultural land use. This approach is very important when a precautionary principle is applied to prevent actions that could deteriorate environmental conditions, and the causal link between such activities and the impact has not been fully confirmed. Thus, for example, some scenarios of the agricultural development proposed by the European Union should, according to Werner’s and Zander’s analysis, lead to environmental threats. By applying the proposed procedures we have the opportunity to correct potential trends of development before the real environmental impacts are observed. The protective role of shelterbelts against wind erosion and severe climatic phenomena has been known for a long time. Chapter 13 discusses the synthesis of the various environmental services of shelterbelts and reviews methods ensuring their efficiency for management of environmentally negative effects of agriculture. The methods of planting trees to increase the value of shelterbelts for environmental protection, thereby ensuring their multifunctionality, are presented. Methods of shelterbelt classification using satellite images are examined in Chapter 14. Such methods enable surveys of shelterbelts to be made in large areas of the countryside. The prospects of agricultural landscape ecology development are discussed in Chapter 15. Barrett and Skelton conclude that although science will yield new environmentally friendly agricultural technologies, sustainable development depends on the abilities of farmers to utilize the achievements of that science. Thus, efficient methods of modern knowledge dissemination are of the utmost significance for rural landscape management.

OUTLOOK The brief review of recent achievements in ecology presented in this book clearly demonstrates that landscape ecology is now passing beyond the threshold from recognition of various basic processes to feasibility for their management in order to attain desired goals. Such transformations are not only brought about by development of knowledge but also are accompanied by changes in nature-protection paradigms

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and decision makers’ growing acknowledgment of the usefulness of landscape ecology for implementation of sustainable development in rural areas. Detailed documentation of that situation is presented in Chapter 16.

REFERENCES Brouwer F. M., Thomas A. J., Chadwick M. J., Eds., 1991. Land Use Changes in Europe, Kluwer Academic Publishers, Dordrecht. 528 pp. Forman R. T. T., Godron M., 1986. Landscape Ecology, John Wiley & Sons, New York. 619 pp. Haines-Young R. H., Potschin M. B., 2000. Multifunctionality and value, in Multifunctional Landscapes, J. Brandt, B. Tress, G. Tress, Eds., Centre for Landscape Research, Roskilde, 111–118. Naveh Z., Lieberman A. S., 1984. Landscape Ecology — Theory and Application. SpringerVerlag, New York. 356 pp. Odum E. P., 1953. Fundamentals of Ecology. W.B. Saunders, Philadelphia. 384 pp. Ryszkowski L., 2000. The coming change in the environmental protection paradigm, in Implementing Ecological Integrity, P. Crabbe, A. Holland, L. Ryszkowski, L. Westra, Eds., Kluwer Academic Publishers, Dordrecht, 37–56. Troll C., 1950. Die geographische Landschaft und ihre Erforschung. Studium Generale (Heidelberg) 3: 163–181. Troll C., 1968. Landschaftsökologie, in Pflanzensoziologie und Landschaftsökologie, R. Tuxen, Ed., Junk, The Hague, 1–21. Turner II B. L., Clark W. C., Kates R. W., Richards J. F., Mathews J. T., Meyer W. B., 1990. The Earth as Transformed by Human Action. Cambridge University Press, Cambridge. 713 pp. · przyrody (On guard of nature) [in Polish]. Pan´ stwowa Rada Wodziczko A., 1948. Na strazy Ochrony Przyrody, Kraków.

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CHAPTER

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Development of Agriculture and Its Impact on Landscape Functions Lech Ryszkowski and Janusz Jankowiak

CONTENTS Introduction................................................................................................................9 Impacts of Agricultural Practices on Landscapes...................................................12 Agricultural Landscape Management for Control of Environmental Threats .......17 Prospects of Landscape Management in Programs of Sustainable Development ..................................................................................20 References................................................................................................................24

INTRODUCTION It seems obvious that human activities in pursuit of safe food supplies, more comfortable housing, resource exploitation, easier transport of people and goods, and so on have transformed nature. Long ago, when population density was low and people lived in small groups separated by vast ranges of wilderness, visible impact on environment appeared only locally, and degraded sites eventually regenerated after their use was abandoned. Ecologically, primeval people differed from other mammals by only one very important skill — use of fire — which sometimes had remarkable impact on the local landscape. The extinction of the large flightless birds about 50,000 years ago in Australia may be interpreted as the result of habitat destruction by fires ignited by primeval humans (Miller et al. 1999). Restricting living activities to a confined area for long periods of time resulted in landscape transformations evidenced, for example, by changes in animal communities under the pressure of hunting or gathering. Stiner et al. (1999) showed that the long-term dependence of paleolithic humans on relatively slow-maturing animals, such as tortoises or edible mollusks,

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caused a decline in their size, a possible sign of overexploitation. Ecologically, such impacts are similar to the broad category of animal influences on habitat, such as overgrazing of plant cover by ungulates confined to an island. Improvement of paleolithic technology led to development of tools that increased work efficiency and increased human options to change landscapes. To ensure prosperity, people subjugated nature for profits that enabled higher standards of living. A crucial event in the subjugation of the countryside was the beginning of agriculture about 10,000 years ago in both the Fertile Crescent and China (rice cultivation) and later in other parts of the world (Pringle 1998). The accumulation of surplus food enabled large settlements and work division, which led to development of complex social organization. The transformation from the hunter-gatherer lifestyle was a slow process, lasting millennia. Inhabitants of southern Egypt used grinding stones as well as mortars and pestles and harvested wild barley and other grass seeds with stone or bone sickles nearly 18,000 years ago (Boyden 1992). In the Fertile Crescent 13,000 years ago, people used sickles for harvesting wild cereals and cultivated some cereals, but at the same time many were still hunters and gatherers (Boyden 1992, Pringle 1998). In large early neolithic settlements excavated in Anatolia, Turkey — such as Asikli, founded about 10,000 years ago — people lived mostly by hunting and gathering. In a large settlement of 2000 families founded about 1000 years later, in Catalhöyük, inhabitants ate both wild and cultivated plants (Balter 1998). About 9000 years ago the main crops, such as einkorn wheat, emmer wheat, barley, lentil, and pea, were domesticated (Lev-Yaduni et al. 2000), and the first successful human attempts to subjugate landscape were made. The progress of agriculture was achieved by trial and error with the focus on yield increase. The scientific basis for plant cultivation and animal husbandry was developed only about 150 years ago, while the environmental consequences of agriculture were recognized only during the last 30 years. Attempts at agricultural landscape management for sustainable development of rural societies are just now being undertaken. The consequences of the agricultural revolution, which is the cornerstone for development of civilization, included formation of a complex social organization that relied on class differentiation. The important feature of this transformation was full-time craft specialization, which in the long run provided positive feedback mechanisms for subjugation of nature, and led to the creation of modern technologies that changed the face of the Earth. At the same time, peasants could focus activities only on farming and became more and more dependent on other class services (protection, trade, production of tools). That change enhanced their non-nomadic lifestyle, the activities of which in turn caused accumulated impact on the environment. For example, soil erosion started to appear in the Mediterranean hillsides as a result of forest clearing, continuous cultivation of large areas, or overgrazing. Such soil degradations were noted by Homer in the 9th century B.C. (Boyden 1992). Maintenance of soil fertility was crucial for intensification of agricultural production. In valleys of major rivers (the Nile, Tigris, Euphrates, and others), recurrent floods brought nutrient supplies each year. Soil fertility was sustained by natural

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processes, and cultivation skills and irrigation techniques of peasants ensured constant yields. Under such conditions, the agriculture provided such surplus food supplies that the great urban states developed in Sumerian Mesopotamia, ancient Egypt, and other river civilizations. Their sustainability was endangered by salinization or by wars destroying the irrigation systems and exterminating the peasant population. In upland areas, peasants had to face the problem of nutrient replenishment. Conversion of forests or grasslands into cultivated fields was accomplished in various ways in the different regions of the world, but one can distinguish a general trend of agriculture intensification. Slash-and-burn agriculture occurred at the stage of development when population density was very low and vast areas of pristine ecosystems were available for conversion. The next step, alternating two-field system (crop, fallow), was made possible by the use of farm animal manure, which intensified land use for crop production. The third step relied on the three-field rotation, in which on one field an overwintering crop was followed by a spring crop and then left fallow. When mineral fertilizers became readily available, the fallow field was eliminated from the crop rotation pattern. The cultivation of cereals, row crops, and pulse crops in rotation without intensive application of chemicals is usually referred to as traditional rotational agriculture. In this system, the recycling of nutrients sustaining soil fertility is maintained by rotation of pulse crops (especially legumes) and organic fertilizers produced within the farm, although some inorganic nutrient inputs can constitute a factor of production intensification. This method was the most intensive form of cultivation before industrialized agriculture gained momentum in the second half of the 20th century, and brought with it intensive use of mineral fertilizers and pesticides, more highly productive cultivars, and total mechanization of tillage. The driving force for agricultural development has been continuously increasing input of energy, at the beginning by human labor, draft animals, and fire, then by harnessed wind and water energy in mills and application of more efficient tools produced by craftsmen. When those craftsmen were replaced by engineers who applied scientific achievements, chemical, electrical, and nuclear energy sources became available for increasing agricultural production and shielding crops from pests, pathogens, harmful climatic conditions, and other obstacles to effective cropping. Boyden (1992) pointed out that the ratio of energy inputs for cropping to energy output (energy value of produced product) in primitive farming societies ranged from 1:15 to 1:20. The same ratio in modern agriculture in the U.K., Holland, or the U.S. ranges from 1:0.5 to 1:0.7. Thus, without very substantial input of energy for management modern agriculture cannot provide high yields. Ryszkowski and Karg (1992) estimated that under conditions of moderately intensive agriculture the greatest contribution to energy subsidies provided by farmers for cereal cultivation was made by industrial fertilizers. With input of 60 kg N·ha–1, 70 kg P2O5·ha–1 and 100 kg K2O·ha–1 the energy costs of fertilizer production amounted to 40% of total subsidies. Energy subsidies in fuel were almost 28% and machinery amortization (22%) ranked third. About 87% of energy subsidies in the

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situation examined were spent on goods produced outside the farm. The maintenance of such a situation was facilitated by the human population harnessing more and more energy fluxes. Agriculture became closely tied to activities of other sectors of society. Reciprocal and close relationships between agriculture and industry, trade, and other human activities recently attained its full expression in industrialized agriculture. Human labor was replaced by work of machines, regeneration of nutrients by inorganic fertilizers, biological control of pests and pathogens by use of pesticides, water problems by drainage and irrigation, and so on (Edwards et al. 1993). Thus, many obstacles to crop production are under the farmer’s control in modern agriculture, and agroecosystems become to a large extent controlled by humans. It is not suprising, therefore, that agriculture has substantial impact on structure and function of the landscape. The impacts of agriculture on landscape features are connected with shielding crops against detrimental factors on the one hand, and with the environmental consequences of applied technologies on the other hand.

IMPACTS OF AGRICULTURAL PRACTICES ON LANDSCAPES During the long period of agriculture development, focus was first directed on practical guidelines for keeping stable yields; then, when scientific grounds for production were discerned, the spectacular growth of yield was achieved. With the exception of the last two or three decades, agricultural activity was valued as purely beneficial for humanity, and almost nobody thought that farmers’ activities could threaten the environment. Conversion of forests or grasslands into cultivated fields changed, of course, the structure of landscape as well as endangered the existence of some plant and animal species. But until industrialized agriculture was developed and global environmental problems were caused by industry and urbanization, the nature conservancy programs assumed that it was possible to shield biological diversity from human influences in national parks, reserves, or other protected habitats. When threats to the environment attained global expression (Hannah et al. 1994, IUCN 1980, Lubchenco 1998, Pimentel and Edwards 2000, Ryszkowski 2000, Vitousek et al. 1997a,b, Watson 1999, and others) the need for reconciliation of human activities with protection of nature was recognized. The conviction is slowly growing that it is the way in which natural resources have been used, not the fact that they are exploited, that has resulted in environmental degradation. A new paradigm for nature protection is proposed that maintains that nature should not be separated from socioeconomic activities but that instead the two should be reconciled (Ryszkowski 2000). The management of landscape processes can be a useful approach to achieving this goal. While increasing production, farmers subsidize energy to simplify plant cover structure within both cultivated fields (selection of genetically uniform cultivars and weed elimination) and agricultural landscape (elimination of hedges, stretches of meadows and wetlands, small mid-field ponds). Animal communities in cultivated fields are also impoverished. Farmers interfere with matter cycling in agroecosystems

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directly by input of fertilizers, pesticides, etc., or indirectly by changing water cycling and decreasing holding capacities of soils for chemical compounds. In addition, agricultural activity often leads to decrease of humus contents. Increased use of farm machinery enables not only stronger impact on soil but also land surface leveling, modification of water drainage, etc., which causes changes in geomorphological characteristics of terrain. These effects of farm activity result in the development of a less complex network of interrelations among the components of agroecosystems. As a consequence of this simplification, relationships among agroecosystem components are altered, so that there is less tie-up in local cycles of matter. Thus increased leaching, blowing off, volatilization, and escape of various chemical components and materials from agroecosystems should be expected (Ryszkowski 1992, 1994, Ryszkowski et al. 1996). Many environmentally significant effects of agriculture intensification are connected with the impoverishment or simplification of the agroecosystem structure. However, to obtain high yields, farmers must eliminate weeds, control pests and pathogens, be assured that nutrients are easily accessible only for cultivated plants during their growth, increase mechanization efficiency, etc. Therefore, agricultural activity aiming at higher and higher yields leads inevitably to the simplification of agroecosystem structure, which in turn causes further environmental hazards. Such ecological analysis leads to a conclusion of major significance for the sustainable development of rural areas: applying intensive means of production, farmers cannot prevent such threats to the countryside as leaching, blowing-off, volatilization of various chemical compounds which causes increased diffuse pollution of ground and surface waters, evolution of greenhouse gases (N2O, CO2, CH4), and water or wind erosion. Biological diversity is also impoverished. Clearly, although farmers can moderate the intensity of these processes through careful selection of crops and tillage technologies, they are unable to eliminate them entirely, regardless of the farming system — industrialized, integrated, or organic. These ecological implications can be evidenced by the analysis of the agriculture development in the European Union (EU) within the framework of the Common Agricultural Policy (CAP). The main objective of the CAP was to ensure agricultural self-sufficiency for countries suffering food shortages during World War II. To fulfill this goal, the CAP was proposed in the late 1950s and started to operate in the late 1960s. Guaranteed high prices were fixed each year for selected products, such as cereals, beef, and milk products. Quotas were later imposed and guaranteed prices were lowered. Other mechanisms were grants for land improvement, customs protection of agricultural commodities, low-interest loans for investment, and wellorganized extension of research services, among others. This protectionist policy encouraged intensive agricultural technologies, which resulted in a substantial increase in production. For example, the average yield of wheat for all countries of the EU rose during the period 1975 to 1991 from 3.2 t–ha–1 to 4.9 t–ha–1, that is, by 53%. In the same period, the wheat production in the Central and Eastern European Countries (CEEC) increased by 18% (Stanners and Bourdeau 1995), although, as in the West, great differences between countries were observed. The average production of wheat in Poland was 23% lower than the average for the total EU, but

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the difference is much higher if one compares yield per hectare with the leading EU wheat producers such as the Netherlands (7.0 t–ha–1), France, Belgium, the U.K., Denmark, and Ireland, where the average wheat production was about 6.0 t–ha–1 (Stanners and Bourdeau 1995). The success of the CAP led to two constraints: one economical and the second one concerning environmental problems. Advances in agricultural technology led to overproduction, and surpluses were stored, which introduced a new burden on the EU economy. The annual rate of increase in agricultural production was 2 to 3% until the mid-1980s, while the rate of increase in consumption was about 0.5% (Laude 1996). Production surpluses accumulated, causing storage problems. To address this situation, proposals to increase production were introduced, such as production quotas, set-aside programs, and lower frontier protection. These issues and other economic problems led to reforms of the CAP in 1992. Price-supporting mechanisms were lowered, while emphasis was placed on decoupling support for farmers from production by tying gains to levels more balanced with market demand. Environmental concerns were also taken into account in the new CAP policy. The negative environmental effects of the previous CAP policy are now quite well recognized (Stern 1996). Intensification of agriculture caused environmental threats in the EU. The CAPsupported increase in farm sizes was related to more efficient use of labor hours and equipment as well as to lower costs for cultivation of large fields not segmented by shelterbelts, open drainage ditches, etc. Lack of permanent plant cover and large open fields exposed to wind and precipitation increased soil erosion processes. Presently in Europe, about 115 million ha suffer from water erosion and 43 million ha suffer from wind erosion. Water erosion is most severe in the Mediterranean region while wind erosion causes serious damage in the southern Ukraine and regions close to the northwest coast of the Caspian Sea (European Environment Agency 1998). Agricultural land comprises up to 70% of total territory of the Ukraine, and arable land cover is 55% of the country area (Voloshyn et al. 1999). Thus, the majority of the countryside in the Ukraine has been almost totally converted into arable land that is tilled with heavy machinery. The water balance is tight, and the central and southern parts of the country suffer water deficits. About 43% of the total arable land is threatened by soil erosion (wind and water), and in productive regions of black soils this figure rises to 70% (Voloshyn et al. 1999). According to estimates of Medvedev and Bulygin (1996), about 500 million metric tons of soil is annually lost from cultivated fields. Because of erosion processes, the potential fertility of soil is lowered by 1.2 times in weakly eroded soils, by 1.4 times in moderately eroded soils, and by 1.6 times in strongly eroded soils. In recent years, because of economic crisis, lower doses of fertilizers and pesticides are used and the intensity of mechanization has decreased. Nevertheless, problems of water, erosion, and soil pollution are still significant. Another serious environmental threat in some European countries (Eastern Germany, Poland, Hungary) is water shortage in rural areas. The threats caused by water deficits are not as spectacular as air pollution impacts; nevertheless, they constitute a real menace during warm and especially dry plant growing seasons. In Poland,

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Figure 2.1

15

Change in Polish grasslands area 1970–1989. Over a period of 18 years, approximately 126,000 ha of grasslands were lost (3%) because of drainage and peatbog reclamation (from 4,166 million ha to 4,040 million ha). (Modified after Denisiuk et al. 1992.)

mean annual precipitation is 717 mm if corrections for sampling error estimates are considered. The uncorrected value of annual precipitation was estimated at 599 mm (Gutry-Korycka 1978). In the central part of Poland, about 80% of precipitation is used for evapotranspiration (Kosturkiewicz and Ke˛ dziora 1995). The situation indicates a very tight water balance, and even a small variation in the ratio of precipitation to evapotranspiration caused by climatic conditions could have a great ecological and economic impact. Low runoff resulting from tight water balance delimits the area of surface water shortage, which amounts to 120,000 km2, that is, 38% of the total area of Poland. In this area, located in the Central Plain, annual water runoff is less than 2 dm–3·s–1·km–2 (Kleczkowski and Mikulski 1995). Climatic conditions have not changed over the last centuries, and, therefore, the increasing water shortage can be attributed to the fast removal of precipitated water by developed drainage systems. Thus, agricultural production intensification without respect for maintenance of water balance, ensuring water storage for the warm season of the year, not only leads to economic problems but also affects the structure of the landscape. Many lakes, small ponds, and wetlands disappeared during the 20th century (Kaniecki

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1991). Changes in vegetation have been observed, and, in particular, many wet meadows have disappeared in the last 30 years (Figure 2.1). In an 18-year period, about 126,000 ha of grassland disappeared as a result of drainage and peatbog reclamation (Denisiuk et al. 1992). The total grassland area decreased from 4.166 million ha to 4.040 million ha (Denisiuk et al. 1992). The change in moisture conditions endangered many plant communities; many plant species common to grasslands recently have become rare. Drying grasslands have also endangered many animal species. Similar situations have been observed in other European countries. Losses of wetlands observed over the last 100 years are continuing despite protection programs launched in many countries. At present the least wetland loss is in northern Europe and the greatest wetland loss is in the south (European Environment Agency 1998). In Denmark, from 1954 to 1984, 27% of small water reservoirs were eliminated (Bülow-Olsen 1988). The diffuse pollution of ground water started to appear in the early 1980s in regions of intensive agriculture in all of the EU countries (OECD 1986). In Germany, in 1985, for example, more than 50% of private water supply systems and 8% of public water works provided water contaminated with N–NO3– above World Health Organization standards (Kauppi 1990). High concentrations of nitrates exceeding 50 mg per liter of soil solution were detected in Germany, northern France, eastern England, northwestern Spain, northern Italy, and Austria. Very high nitrate concentrations were detected in Denmark, the Netherlands, and Belgium (Stanners and Bourdeau 1995). A recent survey of ground water pollution in Europe showed that 87% of the agricultural area in Europe has nitrate concentrations above the guidelevel value of 25 mg·dm3 (Com 1999). High concentrations of nitrates are caused almost entirely by the use of fertilizers and manure. However, local nitrate pollution is caused by municipal or industrial effluents. Thus, in the late 1980s it appeared that modern intensive agricultural practices had brought with them threats to the environment and that the CAP of the EU should be changed by introduction of more environmentally friendly technologies. This situation proved, almost experimentally, that agriculture cannot be considered only in terms of plant and animal production and economy, but that the environmental aspect of these activities should also be taken into account. The other environmental threat brought by agriculture intensification is soil salinization, which appears in the Mediterranean and southeast Europe (Hungary, Romania, the Ukraine, Russia). Salinization appears presently in an area of about 29 million ha (Szabolcs 1991). Irrigation is the main anthropogenic factor influencing salt accumulation under semiarid or arid climatic conditions. Other environmental changes caused by agriculture intensification include loss of soil organic matter, acidification, and soil compaction (Van Lynden 1995). Recognition that environmental threats are increasing forced EU administrators to change the Fifth Action Programme on the Environment (5EAP) to tackle growing problems of environment deterioration, among which ground-water pollution and depletion as well as impoverishment of biological diversity are quite serious. The use of some economic instruments to enhance the control of environmental threats caused by agriculture was proposed by the EU in the new CAP. Measures were

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proposed to promote extensive production methods, set aside of parcels, and codes of good agricultural practice. But the integration of environmental concerns into agricultural practice still presents many difficulties. Nevertheless, environmental issues have become a major concern of the CAP, and a strong focus is placed on the need to integrate farming practices with environment protection “to safeguard the environment and preserve the countryside” (Com 1999). According to the new CAP formulated by the Commission of the European Communities, sustainable agriculture development is founded on five main objectives: competitiveness of production, food safety and quality, fair standards of living for the agricultural community with stabilized incomes, protection of environment, and job opportunities for farmers and their families (Com 1999). The new approach to agriculture development presented by the CAP is shown by the emphasis on holistic treatment of all processes driving agriculture. The landscape approach is clearly recommended, therefore, because it enables identification and integrated analysis of all processes. From this standpoint, “policy choices can be more easily made to express the desired direction for development” (Com 1999). Thus, landscape analysis was recognized by policy makers as a useful tool.

AGRICULTURAL LANDSCAPE MANAGEMENT FOR CONTROL OF ENVIRONMENTAL THREATS Efficient higher control of environmental threats from agriculture could be achieved by structuring agricultural landscape with various nonproductive components such as hedges, shelterbelts, stretches of meadows, riparian vegetation, and small ponds. Therefore, any activity to maintain or increase landscape diversity is important not only for aesthetics and recreation, but even more so for environment protection and, by the same token, for the protection of living resources in the countryside (Ryszkowski 1994, 1998). The above considerations lead us to conclude that activities aimed at optimizing farm production and environment as well as protecting biodiversity should be carried out in two different but mutually supportive directions. The first component involves actions within the cultivated areas whose objective is to maintain the possibly high level storing capacities of soil and to preserve or improve its physical, chemical, and biological properties. Such actions include agrotechnologies, which increase humus resources or counteract soil compaction, and rely on differentiated crop rotations. Important effects of humus resources augmentation would be improved water storage capacity, more intensive processes of ion sorption, etc. Integrated methods of pest and pathogen control and proper application of mineral fertilizers adapted to crop requirements and to chemical properties of soil help facilitate the same degree nonpoint pollution. The effectiveness of such directed activities, which could be called methods of integrated agriculture, depends on good agricultural knowledge. That activity will increase farm competitiveness on the market but cannot ensure the elimination of negative side effects of agriculture on the environment.

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The second component of the integration program of farm production and environment protection is the management of landscape diversity. It consists of such differentiation of the rural landscape so as to create various kinds of so-called biogeochemical barriers, which restrict dispersion of chemical compounds in the landscape, modify water cycling, improve microclimate conditions, and ensure refuge sites for living organisms. In landscapes having a mosaic structure, greater amounts of fertilizers can be applied without subsequent water pollution problems (Ryszkowski 1998a) than can be used in a homogenous structure composed of arable fields only. This conclusion is very important for the program of sustainable development of the countryside. Implementation of those ecological guidelines into the integrated agriculture policy will help develop new environment-friendly agrotechnologies that at the same time enable intensive production balanced with the ability of natural systems to absorb side effects of agriculture without being damaged. By saving natural capital of resilience capacities of the landscape, farmers will increase competitiveness of their farms in a manner similar to that described by Jacques Delors, president of the European Commission, in a white paper (1993) that maintained that improved environmental performance in an industry could increase its competitiveness in the world market. Such a policy requires redefining ideas accepted up to now. Emphasis on increased production and its economical protection without much respect for interrelations of processes and interests should be changed to a more holistic approach that includes landscape issues. The heart of the dilemma at the national level is the failure of economies to elaborate efficient ways to incorporate environmental costs into proposals for rural area development. Recent progress in agroecology and especially studies on agroecosystems and rural landscape functions such as energy flows, matter cycling, and biodiversity maintenance have shown that the following threats to environment and protection of living resources cannot be controlled only at the farm level but must also be curbed by management of the landscape structure diversity: • • • •

Decreased water storage Increased pollution from nonpoint sources Soil erosion Impoverishment of plant and animal communities

The protective activities within the farm can only moderate generation of those threats (e.g., by reasonable use of fertilizers, regardless whether organic or industrial). Because of interconnectivity of water fluxes in phreatic aquifer of the whole watershed, one can observe widespread ground water migration of chemicals leached from soil of cultivated fields, or, due to large ranges of biota dispersion, the protective activities within the small farm are not sufficient to achieve successful biodiversity protection. Thus, protection activities carried out at the landscape level should enhance environmentally friendly technologies applied within the farm. The following activities can be recommended to increase the control of threats at the landscape and agroecosystems level (Ryszkowski and Ba l azy 1995).

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• Increase the water storing capacities in the landscape by introducing mid-field afforestation networks, forming small water reservoirs with controlled outlets, and enhancing humus resources. • Develop efficient technical plants for sewage treatment combined with control measures of diffuse pollution by biogeochemical barriers at the watershed level. Technical and ecological systems of pollution control should enhance their efficiencies by reciprocal support. • Increase erosion control by propagating anti-erosive tillage practices and crop rotation patterns, as well as by structuring landscape with mid-field afforestations and strips of grassland. • Augment application of organic fertilizers and crop rotation patterns, enriching soil in organic matter. • Protect or restore refuge habitats for biota and ensure their connectivity by networks of ecological corridors. • Adjust the application of artificial fertilizers to levels balanced with cultivar needs and introduce biochemical barriers to control spread of unused plant nutrients. • Apply the integrated plant protection methods enhancing effectiveness of biological control by introducing refuge sites for predators.

Higher control efficiency of environmental threats from agriculture could be achieved, therefore, by structuring landscape with various nonproductive components such as shelterbelts, hedges, stretches of meadows, riparian vegetation strips, small mid-field ponds or wetlands, and so on. Natural compatible structures that assist in controlling matter cycles in agricultural landscape are of great importance for enhancing the countryside’s resistance to degradation. Various plant cover structures such as hedges, shelterbelts, stretches of meadows, and riparian vegetation strips are of special interest. They can be easily planted. The provision of such biogeochemical barriers in the landscape is not expensive, and they could provide economic benefits (e.g., timber, herbs, honey, etc.) as well as fulfill some societal needs (hunting, photography, mushroom and berry picking, etc.). Very important from the point of ecological engineering, the biogeochemical barriers exert controlling effects on nonpoint pollution. Mid-field water reservoirs also intercept chemical substances, immobilizing them in bottom deposits, where they are subjected to transformation by biogeochemical processes. The role of small mid-field ponds, neglected and often treated as wastelands, is particularly significant for more efficient use of fertilizers. They can serve as a tool for modification of matter cycling because the chemical compounds leached from fields could be returned to arable fields with sediment. Such forms of field fertilization were recommended long ago in Poland by General Dezydery Ch l apowski in his book on agriculture, published in 1843. The results of investigations concerning the functioning of landscapes led to the conclusion that a purposeful introduction of the biogeochemical barriers such as forest patches, shelterbelts, small mid-field ponds, and stretches of meadows could effectively prevent or limit the spreading intensity of various threats to the environment. Diversity of the agricultural landscape is the root for the control of diffuse pollution, maintenance of biodiversity, and enhancement of its resistance to various threats.

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PROSPECTS OF LANDSCAPE MANAGEMENT IN PROGRAMS OF SUSTAINABLE DEVELOPMENT The majority of landscape studies deal with the description or modeling of patterns of change in land-use forms due to human actions (e.g., Latesteijn 1994, Lambin et al. 2000 and many others). Approaches concentrated on either a single process (e.g., deforestation, urbanization, desertification) or on one aspect of the driving processes (economic, political, environmental deterioration, etc.). One of the best reviews of the state of art in studies on land-use changes was provided by Turner et al. (1990). The change in human population during the last 300 years and its environmental impact on various ecosystems are well addressed in this study, which includes case studies of regional transformations. This analysis shows that human transformation of landscapes is caused by a complex interplay of behavioral, technological, social, and political factors affecting human demands for resources and living conditions. The mix of these factors has changed in time as well as in geographical scale, and changes are now beginning to proceed at such high rates that their impacts are being recognized in day-to-day observations of landscapes. Although various enacted policies have an important role in driving land-use changes, it is doubtful if the simple explanation for the observed changes can be found among characteristics of human population activities (Turner et al. 1990). Energy sources at the disposal of human societies for performance of useful work can be partitioned in various ways, depending on the interplay of technical, societal, and political characteristics of communities. Those interactions evolved throughout history under the pressure of both internal and external factors. This process is illustrated well by the evolution of the CAP. The need to safeguard food supplies resulted in a policy protecting increased agricultural production, and for a period of about 20 years this driving mechanism of agricultural development determined its impacts on land-use changes in Western Europe. Environmental problems in the late 1980s and 1990s clearly demonstrated that ignoring the relationship of the human population to the environment was a mistake. Restriction of analysis to only the level of societal interactions therefore cannot lead to discovery of the driving mechanisms. According to the hierarchical systems theory, driving mechanisms can be discerned if one analyzes the total system into which the studied subsystem is embedded (O’Neill et al. 1986). Thus, not only should the socioeconomical processes be sought in an attempt to pinpoint the driving forces responsible for landuse changes, but environmental processes also should be involved in the analysis. Feedback between land-use changes and processes of solar energy partition for various processes of matter cycling, climate formation, and biological organization is particularly useful for discerning control mechanisms of landscape changes. Landscape in this context is considered not as an aggregated set of landforms but rather as a physical system inextricably linked to human activities that have shaped it. In most studies, the negative environmental effects of land-use changes were described, such as erosion, desertification, salinization, or biodiversity losses, when pristine or semi-natural landscapes are converted to cultivated fields and intensification of land

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use increases. The possibility that human actions subjugating landscapes could simultaneously with alternations of habitats actually enhance processes that counterbalance their detrimental environmental effects is still poorly recognized. That situation persists despite the fact that the concept of sustainability is broadly discussed, and it is obvious that sustainability of the system could be maintained only if system-deteriorating processes are counterbalanced. A short description of such possibilities suggested by modern landscape ecology studies is presented below. An increasing number of studies show that permanent vegetation strips can control migration of chemical compounds leached from cultivated fields with ground water (see published proceedings of conference on buffer zones edited by Haycock et al. 1997). Studies on riparian vegetation strips, shelterbelts, and meadow stretches have shown that when the ground- or surface water outflow from neighboring cultivated fields passes through those biochemical barriers, the concentrations of many chemical compounds decrease. Many studies show that nitrate concentrations in ground water from beneath all studied meadows and shelterbelts were significantly lower than those in ground water under adjoining fields. In some areas studied, the reduction in nitrate concentrations in ground water under the shelterbelts was 34-fold (from 37.6 mg N–NO3·dm–3 to 1.1 mg N–NO3·dm–3; Bartoszewicz and Ryszkowski 1996). The studies of Ke˛ dziora et al. (1995) disclosed the complex control mechanisms exerted by the biogeochemical barriers. In studies on migration of phosphates across a riparian meadow 80 m wide, separating a cultivated field from the drainage channel, the input of P–PO4–3 with ground water was 5.1 g into the segment of meadow 1 m wide during the vegetation season (March 21–October 31). The output of P–PO4–3 to the channel amounted to 0.5 g. Thus, absorption by meadow during the plant growth season amounted to 4.6 g, that is, 90% of input. Total primary production (aboveand belowground) was estimated for 1336 g·m–2 dry weight (d.w.) biomass. The estimated contents of P in plant tissue was 1.78 mg·g–1 d.w. Thus, the P uptake by plants was equal to 1.81 g·m–2. The grass band (80 m long and 1 m wide) absorbed 145 g of P (80 m2·1.82 g·m–2). Thus, the plan’s uptake of P from ground water incoming from cultivated fields (4.6 g) constituted only 3% of the total amount of P absorbed by plants in the band, and the main source of P for plant growth was obtained from its recycling within the soil-plant system. The mechanisms of internal recycling within the biogeochemical barrier therefore play a very important role determining efficiency of control exerted by the biogeochemical barrier. The cases when the biogeochemmical barriers change from sink to source of chemical compounds (Ryszkowski et al. 1999) can be explained by inefficiency of the internal recycling and its decreased storing capacities, which depend to a large extent on biological processes. Further studies on recycling of elements in the biogeochemical barriers will provide guidelines for control efficiency improvement of diffuse pollution by various biogeochemical barriers. Nevertheless, there is no doubt that in most situations, especially with respect to anions, the biogeochemical barriers control diffuse pollution. Options for management of water resources by manipulating plant cover in the landscape are less recognized. The effects of land cover on microclimatic conditions

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Table 2.1 Evapotranspiration (mm) during the Growing Season (March 21–October 31) under Warm and Dry Climatic Conditions (Mean Temperature 12.9°C, Precipitation 234 mm) in Various Landscape Elements Forms of Land Use Evapotranspiration

Cultivated Coniferous Field Field Field Meadow Shelterbelt C+10% between C+20% between C M A of A Shelterbelts of A Shelterbelts 362

437

558

376

355

390

348

Source: Modified after Ryszkowski and Ke˛ dziora 1995.

Table 2.2 Annual Rate of Ground Water Recharge (mm·y–1) in Watershed Covered by Different Kinds of Plant Cover Meteorological Conditions Precipitation Watershed covered by: Cultivated fields Grasslands Forests

Dry Year

Normal Year

Wet Year

627

749

936

108 0 0

233 155 149

351 271 181

Source: Modified after Werner et al. 1997.

such as air temperature, moisture, and wind speed are well known. Nevertheless, feedback of those modifications on water cycling is not often used for conserving water resources in the agricultural landscape. Thus, for example, shelterbelt planting in a landscape consisting solely of cultivated fields, although increasing evapotranspiration rates of the whole area, protects fields against winds, and decreases their evapotranspiration (Ryszkowski and Ke˛ dziora 1995). Thus, a shelterbelt can be considered a landscape structure that redistributes evapotranspiration in the watershed. Areas under shelterbelts show higher evapotranspiration rates while cultivated fields conserve some water. The shelter effect is greater in dry and warm weather than in wet and cool weather. In landscapes with 10% of the area under shelterbelts, the difference between evapotranspiration rate from open cultivated fields and sheltered fields was estimated to be 7 mm (362 mm to 355 mm), and when shelterbelts covered 20% of the area this difference was 14 mm or 14 liters of water/m2 (Ryszkowski and Ke˛ dziora 1995; Table 2.1). Studies in humid climatic conditions showed differences are not great; nevertheless, the conserved water in sheltered fields can delay wilting of cultivated plants. The large differences in evapotranspiration rates between cultivated fields and afforestations result in substantial differences in the water runoff rates from watersheds. For humid climatic zones, the differences between afforested watershed and cultivated fields under meteorological conditions of a normal year can be equal to 84 mm·year–1 (Table 2.2). In wet years, the contribution of water outflow from cultivated fields to the flood flux is 170 mm (170 liters of water from 1 m2) higher than that from forests.

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Changes in plant cover not only modify evapotranspiration rates and watershed water discharge rates but also influence vertical fluxes of energy leading to air heating (vertical fluxes of sensible energy). Cultivated fields convert much more solar radiation into air heating than do afforestations (Ke˛ dziora and Ryszkowski 1999). Through the change of sensible energy fluxes and evapotranspiration, the plant cover structure of a landscape may modify mesoscale air circulations, cloud formation, and precipitation. Stohlgren et al. (1998) indicated that in the plains of Colorado conversion of natural vegetation into cultivated fields and urban habitats influenced climate and vegetation in adjacent natural areas in the Rocky Mountains. That effect of landscape cover structure on climatic processes is especially interesting with regard to studies on the driving mechanisms of the global climatic change. Many studies have shown that mosaic landscapes composed of cultivated fields and nonarable habitats house much richer and more diverse plant and animal communities than do uniform cultivated fields (see, e.g., Baudry 1989, Karg and Ryszkowski 1996). Those findings indicate that by structuring landscape with various refuge sites farmers could counteract biodiversity impoverishment caused by modern agricultural technologies. There are also many studies indicating that mosaic landscapes efficiently counteract erosion processes (Pimentel 1993). Permanent plant stands reduce runoff to 90% or more and stimulate water infiltration into soil. The most efficient methods of erosion control consist of both within-farm and landscape measures. At the farm level, recommended measures include crop rotations, mulches, no-till, countour planting in hilly areas; at the landscape level, grass strips, hedges, field margins, and shelterbelts are proposed. These two approaches constitute the integrated soil conservation programs (Pimentel 1999). The above discussion of options for counteractions to threats brought by intensive agriculture shows there is a growing body of ecological knowledge indicating that management of agricultural landscape for its structural diversity is becoming the important pillar of the sustainability of rural areas. Contemporary programs of environmental protection should not only aim at introducing environmentally friendly technologies of cultivation within the cultivated field or farm, important though that is; they should also be concerned with the challenge of increasing the resistance or resilience of the whole landscape against widely spreading threats. This challenge could be approached by stimulating natural processes underpinning the control of diffuse pollution, efficiency of water retention, wind and water erosion, heat balance changes, and maintenance of biodiversity. Landscape management that harnesses the natural processes of ecosystem and landscape functioning does not represent a refutation of modern means of agricultural production. Rather it represents a more rational strategy which seeks to meet the objectives of food production and of landscape protection and thus contributes to the sustainable development of the countryside (Ryszkowski 2000). The need for a landscape approach to agriculture development was strongly stressed by Reenberg and Baudry (1999), Ryszkowski (1994, 1998), and Thenail (1996). This claim stems from the recognition that functions of cultivated fields are nested in functions appearing at the scale of landscapes which can be only partially

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modified by actions at the farm level. Thus, for example, a farm constitutes the economical operational unit, while in regard to energy fluxes and matter cycling processes the landscape is a more autonomous unit (Ryszkowski 1998b). To discern the operational relationships between various levels of a hierarchical organization of the landscape constitutes the challenge for landscape ecologists (O’Neil et al. 1986). Disentanglement of those relationships will also have great practical significance. The new CAP policy offers opportunities for integrating agricultural production with environment protection in the form of cross-compliance requirements. This approach requires farmers to observe a set of prespecified land-use conditions and practices in return for the receipt of government payments. These requirements concern introduction of more environmental friendly technologies to withdraw a land from production. Lack of landscape perspective in those requirements makes them less efficient. For example, there are no specific instructions indicating which parcels with respect to landscape functions should be withdrawn in the set-aside program. There is also a lack of regulation concerning landscape planning strategies. It seems that incorporating the landscape approach into proposed regulations of the new CAP policy will enhance its ecological effects. Landscape ecology, therefore, generates not only great scientific interest but also practical interest. Thus, landscape approach to the agriculture has become one of the pillars of sustainability.

REFERENCES Balter M. 1998. Why settle down? The mystery of communities. Science 282:1442–1445. Bartoszewicz A., Ryszkowski L. 1996. Influence of shelterbelts and meadows on the chemistry of ground water. In Dynamics of an Agricultural Landscape. Eds. L. Ryszkowski, N. R. French, A. Ke˛ dziora. Pan´ stwowe Wydawnictwo Rolnicze i Les´ ne. Poznan´ : 98–109. Baudry J. 1989. Hedgerows and hedgerow networks as wildlife habitat in agricultural landscapes. In Environmental Management in Agriculture. Ed. J.R. Park. Belhaven Press. London: 111–124. Boyden S. 1992. Biohistory: The Interplay between Human Society and the Biosphere. Parthenon Publishing Group. Paris. 265 pp. Bülow-Olsen A. 1988. Disappearance of ponds and lakes in southern Jutland, Denmark 1954–1984. Ecol. Bull. (Copenhagen) 39: 180–182. Ch l apowski D. 1843. O rolnictwie. Druk Walentego Stefan´ skiego. Poznan´ . 164 pp. Com, 1999. Direction toward Sustainable Agriculture. Commission of the European Communities. Brussels. 30 pp. Denisiuk Z., Kalemba A., Zaja˛ c T., Ostrowska A., Gawlin´ ski S., Sienkiewicz J., RejmanCzajkowska M. 1992. Integration between Agriculture and Nature Conservation in Poland. IUCN East European Programme. Information Press. Oxford. 162 pp. Edwards C.A., Grove T.L., Harwood R.R., Pierce Colfer C.J. 1993. The role of agroecology and integrated farming systems in agricultural sustainability. Agric. Ecosys. Environ. 46: 99–121. European Environment Agency. 1998. Europe’s Environment: The Second Assessment. Elsevier Science Ltd. Amsterdam. 293 pp.

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Gutry-Korycka M. 1978. Evapotranspiration in Poland (1931–1960) [in Polish]. Przegla˛ d Geograficzny 23: 295–299. Hannah L., Lohse D., Hutchinson C., Carr J., Lankerani A. 1994. A preliminary inventory of human disturbance of world ecosystems. Ambio 23: 246–250. Haycock N.E., Burt T.P., Goulding K.W.T., Pinay G. (Eds). 1997. Buffer Zones: Their Processes and Potential in Water Protection. Quest Environmental. Harpenden, U.K. 326 pp. IUCN. 1980. The World Conservation Strategy. IUCN-UNEP. Gland, Switzerland. 156 pp. Kaniecki A. 1991. Drainage problems of Wielkopolska Plain during last 200 years and changes of water relationships [in Polish]. In Ochrona i Racjonalne Wykorzystanie Zasobów Wodnych na Obszarach Rolniczych w Regionie Wielkopolski. ODR Sielinko. Poznan´ : 73–80. Kauppi L. 1990. Hydrology: water quality changes. In Toward Ecological Sustainability in Europe. Eds. A. M. Solomon and L. Kauppi. International Institute for Applied System Analysis. Laxenburg (Austria): 43–66. Kleczkowski A.S., Mikulski Z. 1995. Water management forecast — State of resources (in · Polish). In Prognoza Ostrzegawcza Zmian S´ rodowiskowych Warunków Z ycia Cz l owieka w Polsce na Pocza˛ tku XXI Wieku. Ed. S. Koz l owski. Instytut Ekologii PAN. Oficyna Wydawnicza, Dziekanów Les´ ny: 35–46. Ke˛ dziora A., Ryszkowski L. 1999. Does plant cover structure in rural areas modify climate change effects? Geographia Polonica 72: 65–87. Kosturkiewicz A., Ke˛ dziora A. 1995. Problems of water management in agricultural areas [in Polish]. In Zasady Ekopolityki w Rozwoju Obszarów Wiejskich. Eds. L. Ryszkowski and S. Ba l azy. Research Centre for Agricultural and Forest Environment. Poznan´ : 73–98. Lambin E.F., Rounsevell M.D.A., Geist H.J. 2000. Are agricultural land-use models able to predict changes in land-use intensity? Agric. Ecosys. Environ. 82: 321–331. Latesteijn van H.C. 1994. Ground of choice: a policy oriented survey of land use changes in the EC. In Functional Appraisal of Agricultural Landscape in Europe. Eds. L. Ryszkowski and S. Ba l azy. Research Centre for Agricultural and Forest Environment. Poznan´ : 289–297. Laude Y. 1996. The Enlargement of the Common Agricultural Policy to the Ten Central and Eastern European Countries. Club de Bruxelles. Brussels. 95 pp. Lev-Yadun S., Gopher A., Abbo S. 2000. The cradle of agriculture. Science 288: 1602–1603. Lubchenco J. 1998. Entering the century of the environment: a new social contract for science. Science 279: 491–497. Medvedev V.W., Bulygin S.J. 1996. The experience of agricultural land conservation in the Ukraine. In Landscape Diversity: A Chance for the Rural Community to Achieve a Sustainable Future. Eds. L. Ryszkowski, G. Pearson and S. Ba l azy. Research Centre for Agricultural and Forest Environment. Poznan´ : 176–179. Miller G.H., Magee J.W., Johnson B.J., Fogel M.N., Spooner N.A., McCulloch M.T., Ayliffe L.K. 1999. Pleistocene extinction of Genyornis newtoni: human impact on Australian megafauna. Science 283: 205–208. OECD. 1986. Water Pollution by Fertilizers and Pesticides. OECD. Paris. 144 pp. O’Neill R.V., DeAnglis D.L., Waide J.B., Allen T.F.H. 1986. A Hierarchical Concept of Ecosystems. Princeton University Press. Princeton. 253 pp. Pimentel D. (Ed.). 1993. World Soil Erosion and Conservation. Cambridge University Press. Cambridge, U.K. 349 pp. Pimentel D., Edwards C.A. 2000. Agriculture, food, populations, natural resources and ecological integrity. In Implementing Ecological Integrity. Eds. P. Crabbe, A. Holland, L. Ryszkowski and L. Westra. Kluwer Academic Publishers. Dordrecht: 337–338.

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Pringle H. 1998. The slow birth of agriculture. Science 282: 1446–1450. Reenberg A., Baudry J. 1999. Land-use and landscape changes — the challenge of comparative analysis of rural areas in France. In Land-Use Changes and Their Environmental Impact in Rural Areas in Europe. Eds. R. Krönert, J. Baudry, I. R. Bowler, A. Reenberg. The Parthenon Publishing Group. Paris: 23–41. Ryszkowski L. 1994. Strategy for increasing countryside resistance to environmental threats. In Functional Appraisal of Agricultural Landscape in Europe. Eds. L. Ryszkowski and S. Ba l azy. Research Centre for Agricultural and Forest Environment. Poznan´ : 9–18. Ryszkowski L. 1998a. Ecological guidelines for the management of agricultural landscapes. In Modern Trends in Ecology and Environment. Ed. R.S. Ambasht. Backhuys Publishers. Leiden. 187–201. Ryszkowski L. 1998b. Guidelines for environment protection against diffuse pollution (in Polish). In Kszta l towanie S´ rodowiska Rolniczego na Przyk l adzie Parku Krajobrazowego im. Gen. D. Ch l apowskiego. Eds. L. Ryszkowski and S. Ba l azy. Zak l ad Badan´ S´ rodowiska Rolniczego i Les´ nego PAN. Poznan´ : 81–88. Ryszkowski L. 1998c. Farm in the agricultural landscape (in Polish). In Dobre Praktyki w Produkcji Rolniczej. Ed. I. Duer. Instytut Uprawy, Nawoz· enia i Gleboznawstwa. Pu l awy: 491–505. Ryszkowski L. 2000. The coming change in the environmental protection paradigm. In Implementing Ecological Integrity. Eds. P. Crabbe, A. Holland, L. Ryszkowski and L. Westra. Kluwer Academic Publishers. Dordrecht: 37–56. Ryszkowski L., Ba l azy S. 1995. Strategy for environment and nature protection in rural areas (in Polish). In Zasady Ekopolityki w Rozwoju Obszarów Wiejskich, Eds. L. Ryszkowski and S. Ba l azy. Zak l ad Badan´ S´ rodowiska Rolniczego i Les´ nego PAN, Poznan´ : 49–64. Ryszkowski L., Karg J. 1992. Energy flow in rye grown in continuous and norfolk rotation cultures. Acta Academiae Agriculturae AC Technicae Olstenensis. Agricultura 55: 201–213. Ryszkowski L., Bartoszewicz A., Ke˛ dziora A. 1999. Management of matter fluxes by biogeochemical barriers at the agricultural landscape level. Landscape Ecol. 14: 479–492. Stanners D., Bourdeau P. 1995. Europe’s Environment. European Environment Agency. Copenhagen. 676 pp. Stern A. 1996. Environment. The mid-field review of the European Union’s Fifth Action Programs. Club de Bruxelles. Brussels. 125 pp. Stiner M.C., Munro N.D., Surovell T.A., Tchernow E., Bar-Yosef O. 1999. Paleolithic population growth pulses evidenced by small animal exploitation. Science 283: 190–193. Stohlgren T.J., Chase T.N., Pilke R.A., Kittels G.F., Baron J.S. 1998. Evidence that local land use practices influence regional climate, vegetation and stream flow patterns in adjacent natural areas. Global Change Biol. 4: 495–504. Szabolcs I. 1991. Salinization potential of European soils. In Land Use Changes in Europe. Eds. F.M. Brouwer, A.J. Thomas, M.I. Chadwick. Kluwer Academic Publishers. Dordrecht: 293–315. Thenail C.B.J. 1996. Consequences on landscape pattern of within farm mechanisms and of land use changes. In Land Use Changes in Europe and Its Ecological Consequences. European Centre for Nature Conservation. Tilburg: 242–258. Turner II B.L. Clark W.C., Kates R.W., Richards J.F., Mathens J.T., Meyer W.B. 1990. The Earth as Transformed by Human Action. Cambridge University Press. Cambridge, U.K. 713 pp.

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Werner A., Eulenstein F., Schindler U., Müller L., Ryszkowski L., Ke˛ dziora A. 1997. Groundwasserneubildung und Landnutzung. Zeitschrift für Kulturtechnik und Landentwicklung 38: 106–113. Van Lynden G.W.J. 1955. European Soil Resources. Nature and Environment 71. Council of Europe Press. Strasbourg. 99 pp. Vitousek P.M., Aber J.D., Howarth R.W., Likens G.E., Matson P.A., Schindler D.W., Schleisinger W.H., Tilman D.G. 1997a. Human alteration of the global nitrogen cycle: sources and consequences. Ecol. Appl. 7: 737–750. Vitousek P.M., Mooney H.A., Lubchenco J., Melillo J.M. 1997b. Human domination of earth’s ecosystems. Science 277: 494–499. Voloshyn V., Lisovsky S., Gukalova I. Reshetnik V. 1999. Ecological-economic problems of land use in the Ukraine. In Land-Use Changes and Their Environmental Impact in Rural Areas in Europe. Eds. R. Krönert, J. Baudry, I.R. Bowler and A. Reenberg. The Parthenon Publishing Group. Paris: 221–234.

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CHAPTER

3

Mitigation of Radiation and Heat Balance Structure by Plant Cover Structure Janusz Olejnik, Andrzej Ke˛dziora, and Frank Eulenstein

CONTENTS Introduction..............................................................................................................29 Heat Balance Components ......................................................................................31 Measurements and Modeling of Heat Balance Components .................................32 Daily Value of Heat Balance Components for Selected Ecosystems.....................35 Seasonal Value of Heat Balance Components for Selected Ecosystems and the Landscape..................................................................................................41 Changes in Heat Balance Components under Changed Climatic Conditions .......48 References................................................................................................................53

INTRODUCTION The Earth’s atmosphere is an extremely important medium that links the other elements of the environmental system. There are permanent fluxes of energy and matter exchange between the Earth’s surface and its atmosphere. All processes occurring on the Earth are possible because of spatial differentiation of potential energy. The realization of each irreversible process is connected with entropy production — in other words, with the increase of “disorder” in a thermodynamic system. With regard to the Earth–atmosphere system, it means that if no energy flux flows into the system from outside, the temperature within the system will equalize and all processes will be stopped. Yet constant flux of solar energy acts as a brush; it removes this disorder from the system by restoring the differentiation of the temperature field because it takes away more entropy than it brings into the system. Thanks to this perpetual solar energy flux (Figure 3.1), the realization of all thermodynamic

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Balance of: radiation heat

Rn= K - K+ L- L

Rn = G + S +LE

water

E+H=P

common element

Figure 3.1

Schematic connection of radiation, heat, and water balances in agricultural landscape.

processes, which are essential for life on Earth, is possible. The most important of these are the matter-cycling processes, especially water cycling. Due to these fluxes, one can consider the atmosphere a mirror, in which the present conditions of the Earth’s surface environment are “reflected.” On the other hand, the condition of the environment can be modified by the state of the atmosphere, both by short- and long-term interactions. Industrial and agricultural development in the 19th and 20th centuries led to unfavorable changes in the natural environment. At present, while these changes are commonly recognized on both the global and local scales, it is important to stop or at least minimize the effects of those processes that have negative effects on the environment. The crucial question is how to manage the landscape to create conditions that will enable us to return (if possible?) to ecological equilibrium (Stigliani et al. 1989, Freedmen 1992, Ke˛ dziora 1999). To answer that question, we first must learn more about interactions between the atmosphere and the Earth’s surface. One of the ways to achieve a better understanding of all the processes that occur in the natural environment is to measure or model them. Results of measurement of energy fluxes create the possibility of parameterization of these processes, consequently leading to development of these models, which can be applied to different environmental conditions. Modeling of heat and water balance components very often has a practical application, e.g., for estimating evapotranspiration on a field scale (Olejnik 1988, Olejnik et al. 2001) and regional scale (Thom and Oliver 1977) by determining the water condition due to land-use condition (Kirchner 1984), or even by forecasting and estimating the yield (Tanner 1981, Gurney 1988).

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One way of describing environmental processes on different scales (from micro to global scale) is by the analysis of energy flux exchange between the Earth’s surface and the atmosphere. The knowledge about these fluxes and their interactions provides information not only about energy exchange in the environment but also about water, carbon, and nutrient balances and can be helpful for their estimation when direct measurements over large areas are difficult or impossible. Therefore, the analysis of heat balance structure is one of the best descriptions of environmental conditions on both local and global scales (Paszyn´ ski 1972, Rosenberg 1974, Kim and Verma 1990, Olejnik 1996). The driving force of energy in water, carbon, or nitrogen cycles and the interactions of these cycles provide a basic framework for understanding the potential feedback of the active surface and the atmosphere. Most of these relationships exert strong biological control on land-atmosphere interactions. Therefore, land-cover and land-use changes are driving variables for understanding energy exchange and, consequently, climate processes on both regional and global scales (Valentini et al. 1999). The landscape is a very complex, open, dynamic system of relationships in which nonlinear processes and feedback mechanisms play an important role. Many of these feedback mechanisms depend on the process of energy and mass exchange between the atmosphere and the Earth’s surface. The so-called surface processes are strongly connected with the transfer of water or water vapor from and into the atmosphere. Part of the water that reaches the Earth’s surface returns to the atmosphere via evapotranspiration and part goes to sea by runoff. The available energy is the most important physical factor that limits the amount of evapotranspiration. On the other hand, the kinds of plants that cover the Earth’s surface as well as the plant development stage are the most important biological factors. For model investigations on heat and water balance structure, both physical and biological factors have to be included in models for all scales — from field to global.

HEAT BALANCE COMPONENTS The middle section of Figure 3.1 shows the heat balance of an active surface. In general, energy exchange processes are driven by solar radiation. The right part of Figure 3.1 shows the radiation balance. The short-wave radiation reaching the Earth’s surface is called global radiation (↓K). The short-wave radiation is partly absorbed by the active surface (soil, plant, water, etc.) but partly reflected (↑K) from the active surface. The ratio of reflected to incoming global radiation is called albedo (α = ↑K/bK) and is one of the most important parameters characterizing the input of energy into agroecosystems, forests, deserts, etc. For example, in natural conditions, high albedo (e.g., 0.3) means that a substantial part of the short-wave radiation energy reaching the ecosystem is reflected and only 70% is absorbed by the active surface. The absorbed short-wave radiation increases the temperature of the active surface, which in turn is reflected as increased long-wave radiation of the active surface (↑L in Figure 3.1). This long-wave radiation is partly absorbed in the atmosphere by the greenhouse gases (water vapor, CO2, etc.). This absorption causes the increased temperature of the atmosphere, which in turn increases the long-wave radiation of the atmosphere. Some of the long-wave radiation of the atmosphere goes to the higher

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atmosphere and to space, but part returns to the Earth’s surface (↓L). If one adds all four fluxes — two incoming (short wave from the sun and long wave from the atmosphere back to the Earth’s surface) and two outgoing (short wave reflected and long wave emitted by the Earth’s surface) — one can construct the radiation balance of an active surface (Figure 3.1). The result of the balance of all these fluxes is the net radiation (Rn), and it denotes energy supply for all processes in the environment driven by natural energy, including photosynthetic processes, which utilize solar radiation for organic matter production. However, metabolic processes may be considered negligible relative to the magnitude of other energy fluxes, and, therefore, it is possible, following the energy conservation law, to write the energy (heat) balance equation as: Rn = Le + S + G

(3.1)

where Rn is net radiation, LE is latent heat flux (L is evaporative heat of water and E is evapotranspiration), S is sensible heat flux, and G is soil heat flux. Evapotranspiration of the plant community (or its energy equivalent, latent heat flux), warming of the soil surface, and consequently, also deeper soil layer (due to conductivity) or convection heating of the atmosphere are well-known processes occurring in the environment. Rn sets the energy utilized by these processes. The partition of net radiation for these processes is described by the heat balance equation and depends on both physical and biological factors that determine environmental conditions: plant type, land-use structure, plant development stage, weather conditions, etc. Through the latent heat flux (or evapotranspiration), there is a direct connection between heat and water balance of an investigated area. Figure 3.1 shows the connections between radiation, heat, and water balances. The links between these balances play a very important role for the complex description of energy-water conditions of the environment and are often used by investigators to calibrate or validate different models for estimating mass and energy exchange processes. At present, many modeling activities use these principles to calculate the mass and energy exchange for several land-use/cover types, from the patch (small area having the same characteristics of habitat) to regional or global scale. Nevertheless, since the concept is relatively new, it has not been tested widely against field measurements of mass and energy exchange, nor has this concept been tested over an assortment of vegetation types. Experimental measurements of biosphere-atmosphere mass and energy exchange have the additional advantage of providing a new synthesis view of ecosystem processes, which allows us to improve our conventional classification of vegetation types and forms, achieving a deeper insight into functional biodiversity at the landscape level (Ke˛ dziora and Olejnik 1996, Valentini et al. 1999, Ke˛ dziora and Ryszkowski 1999).

MEASUREMENTS AND MODELING OF HEAT BALANCE COMPONENTS In the 1990s, developments in micrometeorological technology and theory made it possible to study regularly the interactions between vegetation and atmosphere.

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Recent improvements in the eddy covariance method, which provides a direct measure of biosphere-atmosphere mass and energy fluxes at the ecosystem level, were particularly important for studies (Ryszkowski and Ke˛ dziora 1993b, Tenhunen and Kabat 1999, Ke˛ dziora et al. 2000). In the past, most of our knowledge of carbon, water, or energy exchange in vegetation was based on measurements taken at the leaf level with enclosure chambers or portable cuvettes (Field et al. 1982). With the development of micrometeorological methods, a large change in scale of focus was achieved, moving from the leaf level, species/individual-dependent approach to an integration of overall ecosystem fluxes in a direct, nondestructive way. There are many micrometeorological methods based on physical principles, which allowed measurement of the turbulence components of heat balance (LE and S in Equation 3.1). According to the eddy covariance theory, the eddy flux of any scalar can be written as: Fc = ρc ⋅ w

(3.2)

where Fc is the flux density of scalar c, w is the vertical wind speed, and ρc is the density (or concentration) of the transported species. The overbar represents the mean of product over the sampling interval. The eddy covariance method technique, developed during the 1980s and the 1990s, needs very technologically advanced sensors, and therefore it is not so commonly used. To measure eddy fluxes with this technique, rapid response sensors are necessary. These sensors and incorporated data acquisition systems are able to measure and collect data with very high frequencies (10 Hz and more). To measure heat or mass fluxes, sonic anemometer and open- or close-path gas analyzers are used (Arya 1988). Less technologically advanced sensors can be used for eddy flux measurements using gradient or heat balance methods. To determine the latent and sensible heat fluxes (LE and S in Equation 3.1) measurements of temperature and water vapor pressure in the air at several levels are necessary. For such measurements, adequate electrical psychrometers and cup anemometers can be used. It is known that latent (LE) and sensible (S) heat flux densities are proportional to water vapor and air temperature gradients, respectively (Monteith 1975), as follows: LE = Kv ρ c p γ −1

S = KH ρ cp

∂T ∂z

∂e ∂z

(3.3)

(3.4)

where γ is the psychrometric constant equal to 0.65 hPa·K–1, e is the water vapor pressure [hPa], T is the air temperature [K], ρ is air density equal to 1.25 kg·m–3, cp is the specific heat of air equal to 1004 J·kg–1 ·K–1, and KV and KH are the eddy diffusivities for water vapor and heat, respectively. There are also methods of eddy flux determination that are based on the combination of two methods: gradient (with measurement at few levels) and heat balance

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(Equation 3. 1) (for example, the so-called Bowen ratio method, Olejnik et al. 2001). Using this method, some results of heat balance components determination with respect to land-use conditions are discussed later in this chapter. There are many models that describe explicitly the physical processes in the environment, but to use them on a large or global scale is very difficult because of computer power and input data limitations. Therefore, sometimes an empirical model can be used, and, after the modeling procedure, its results can be coupled with a larger or even global scale model (e.g., GCM) (Kundzewicz and Somlyódy 1993). Even empirical models do not explain different phenomena themselves, but the results from these models can be very helpful by quantitatively describing many environmental processes. One of the considerable limitations for modeling is the data availability for the input data set. There are some quite precise models for heat or water balance components estimation (McNaughton and Spriggs 1985, Holtslag and De Bruin 1988, Beljaars and Holtslag 1991, Wegehenkel 2000), but their application for larger areas is very limited because the input data set needed for these models is very often inaccessible. In some cases it is impossible, by now, to collect the input data, such as moisture or physical properties of soils for a large area at satisfactory resolution. Therefore, it seems that the MBC model recently developed by the Agrometeorology Department of the Agricultural University of Poznan´ (Olejnik and Ke˛ dziora 1991, Olejnik 1996, Les´ ny 1998) is a compromise between the quality and resolution of conclusions and the possibilities of input data set collection and appropriate consideration of physical and biological processes included in the modeling procedure. The resolution of MBC (limited only by land-use data resolution) can be significantly higher than GCM’s resolution, and the input data set is relatively easy to collect for larger areas. This model, or its earlier stage, has been successfully applied on different scales: on the field scale (Olejnik 1988), the catchment scale (Ke˛ dziora et al. 1989), the regional scale (Olejnik and Ke˛ dziora 1991), and the country scale (Ryszkowski et al. 1991, Ryszkowski and Ke˛ dziora 1993). The MBC model is based on the empirical equation that links the Bowen ratio with meteorological parameters and plant development stage. In 1986 an agrometeorological index was proposed (Olejnik 1988), as follows:

[

(

W = 100 D v0.5

)

atn Π 2 f

] [T (s + 0.4)]

(3.5)

where D is saturation vapor pressure deficit in [hPa], v is wind speed in [m·s–1], f is plant development stage (changing from 0 to 1), T is air temperature in [°C], and s is relative sunshine. By definition, the Bowen ratio is equal to β = S/LE. Using the proposed index, the following empirical equation for Bowen ratio estimation was proposed: β(W ) =

12.75 − 0.02 W + 3.7

(3.6)

0919 ch03 frame Page 35 Tuesday, November 20, 2001 6:29 PM

MITIGATION OF RADIATION AND HEAT BALANCE STRUCTURE

35

Finally, from the combination of the Bowen ratio and Equation 3.1, the latent and sensible heat fluxes can be estimated in the MBC model as follows: LE = ( Rn + G) [1 + β( W )]

(3.7)

S = ( Rn + G) [1 + 1 β( W )]

(3.8)

Using the above equations and data about land-use structure, as well as plant cover development stage, the first version of MBC model for areal heat and water balance estimation was proposed (Ke˛ dziora et al. 1989, Olejnik and Ke˛ dziora 1991). Later in this chapter, some results of areal heat balance components estimation with respect to land-use conditions are discussed using the MBC model application. DAILY VALUE OF HEAT BALANCE COMPONENTS FOR SELECTED ECOSYSTEMS Using the above-described methodology, we can measure or model heat balance components (Equation 3.1). During the last decade, many measurements have been made at different sites from the climatic and plant cover viewpoints. This chapter discusses some results of heat balance daily dynamics on the basis of in situ investigations in different conditions carried out by the Agrometeorology Department of the Agricultural University in Poznan´ . The measurements were carried out in different climatic zones to study the impact of climatic conditions on heat balance components. In general, the structure of heat balance is formed mainly by three factors: • Amount of solar energy reaching the active surface depending on latitude and daily course of sunshine • Physical features of the active surface, mainly richness and structure of plant cover • Habitat moisture, which controls the intensity of evapotranspiration and thus the intensity of latent heat flux

An active surface is any surface through which energy and matter are passing and simultaneously changing their characteristics. For example, solar short-wave radiation is absorbed by the soil and re-emitted as long wave radiation. Similarly, water flowing in the soil as liquid changes its state to gaseous form by evaporation. The typical daily courses of heat balance components on sunny days are presented in Figure 3.2 (Ke˛ dziora et al. 1997). In arid climatic conditions, when the soil surface is covered with very poor vegetation, the sensible heat flux constitutes the main part of net radiation (Figure 3.2A, Table 3.1). The latent heat flux is very small when compared with soil and sensible heat fluxes. The LE/Rn ratio equals only 0.13 (13%) of net radiation, while the S/Rn ratio may be as great as 60%. The Bowen ratio is very high, up to 4.90. Conversely, in humid continental or transitional

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LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Flux density W m-2

Flux density W m-2

36

Rn

A

200 0

S

-200 0 400

2

4

6

8

LE G

10 12 14 16 18

20 22 Hour

Rn

B

200 0

G S

-200

LE 0

2

4

6

8

10 12 14 16 18

20 22 Hour

Flux density W m

-2

600

C

400

Rn

200

G

0

LE

-200

S

-400 -600 0 Figure 3.2

2

4

6

8

10 12 14 16 18

20 22 Hour

Typical 24-h courses of heat balance components in different climatic zones. A — arid zone (Kazakhstan), B — transition zone (Turew, Poland), C — humid zone (Cessieres, France).

climate conditions (Figure 3.2B) the LE/Rn ratio exceeded 90%. In the case of oceanic climate (Figure 3.2C) the LE/Rn ratio was almost 100% (Table 3.1). An entirely different situation was observed in arid or semi-arid climatic conditions, when plant cover existed and water supply was unlimited. When a dry hot area surrounds an irrigated alfalfa field (Figure 3.3), very high latent heat flux was observed. The average daily net radiation on observational days was not higher than about 180 Wm–2, but a very intense evapotranspiration rate, possibly due to irrigation, caused an inversion of temperature and an increase in latent heat, which exceeded 200 Wm–2 on July 17 (Table 3.1). On that day, the LE/Rn ratio was 1.14, while the Bowen ratio was negative and amounted to –0.18. A negative value for the Bowen

0919 ch03 frame Page 37 Tuesday, November 20, 2001 6:29 PM

MITIGATION OF RADIATION AND HEAT BALANCE STRUCTURE

Table 3.1

Heat Balance Components Measured at Different Sites Located in Different Climatic Zones

Site

Date

A

20.08.89 21.08.89 25.08.89 11.07.88 17.07.88 13.07.83 17.08.83 16.05.84 30.06.85 09.08.87 16.07.93 16.07.93 15.07.94 16.07.94 17.07.94

K T

C Z

37

Heat Balance Components [Wm–2] Rn LE S G 55 83 70 60 149 149 65 115 126 106 164 145 181 65 182

–59 +2 –9 –38 –133 –79 –25 –127 –100 –100 –152 –56 –178 –129 –209

–5 –67 –44 –18 –7 –75 –30 37 –12 +2 –6 –77 +13 +48 +39

+9 –18 –17 –4 –9 5 –11 –25 –13 –7 –6 –12 –16 +16 –12

LE/Rn

Ratios S/Rn

S/LE

–1.07 +0.02 –0.13 –0.63 –0.89 –0.53 –0.38 –1.10 –0.79 –0.94 –0.93 –0.39 –0.98 –1.98 –1.14

–0.09 –0.81 –0.62 –0.30 –0.05 –0.50 –0.46 0.32 –0.10 0.02 –0.04 –0.53 0.07 0.74 0.21

0.08 –33.50 4.90 0.47 0.05 0.95 1.20 –0.29 0.12 –0.02 0.04 1.37 –0.07 –0.37 –0.18

In Alma-Ata (A) the climate is continental, arid, with low precipitation, high temperature in summer and very low temperature in winter, low air humidity, and a high percentage of sunshine and high global radiation. In Kursk (K) the climate is less continental. It is humid, with moderate precipitation, temperature, sunshine and air humidity, and a relatively high global and net radiation. In Turew and Müncheberg (M and T) the climate is transitional (between continental and oceanic), with moderate temperature, air humidity, and precipitation, and low sunshine and global and net radiation. In Cessieres (symbol C) the climate is humid, with relatively high precipitation, and moderate sunshine and global and net radiation. In Zaragoza (symbol Z) the climate is warm, semi-arid, with low precipitation and air humidity, high sunshine, and global and net radiation. The names of these cities were used symbolically; the study sites were located near cities in agricultural landscapes.

ratio means that sensible heat flux is oriented toward the active surface, having a positive sign, while latent heat flux of evapotranspiration has a negative sign (water vapor is flowing from the surface into the atmosphere). Therefore, plant cover plays the most important role for the structure of heat balance, because it is the factor by which the evapotranspiration process controls the density of latent heat flux. This conclusion is supported by the case of heat balance structure for July 16 in Zaragoza (Figure 3.3B). The previous day was sunny, with very intense solar radiation and evapotranspiration. It was completely cloudy on July 16, but the evapotranspiration rate remained very high because of a deep temperature inversion over the alfalfa field. On this day, the LE/Rn ratio was extremely high, up to –1.98. The Bowen ratio was equal to –0.37. During a sunny day (15.07) the net radiation was about 180 Wm–2 and daily evapotranspiration was about 6 mm/day. On a cloudy day, the net radiation was threefold lower but evapotranspiration was lower by only about 30 to 40% when compared with the day before (Table 3.1). In such a situation, the

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38

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

800

A

-2

Flux density [W m ]

600 400 200 0 -200 -400 -600 0

2

4

6

8

10 12 14 16 18

20 22 Hour

4

6

8

10 12 14 16 18

20 22 Hour

B

600

-2

Flux density [W m ]

800

400 200 0 -200 -400 -600 0

2

Flux density [W m-2]

800

C

600 400 200 0 -200 -400 -600 0

Figure 3.3

2

4

6

8

10 12 14 16 18

20 22 Hour

24-h courses of heat balance components in semi-arid zone of Zaragoza, Spain during a cloudy day with heat advection (July 16, 1994) in comparison with courses during the sunny days immediately preceding (July 15, 1994) and immediately following (July 17, 1994).

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MITIGATION OF RADIATION AND HEAT BALANCE STRUCTURE

Table 3.2

39

Impact of Landscape Structure on Heat and Water Balance in the Growing Season (March 21 to October 31) in Turew

Landscape Grain crop monoculture Grain crops with shelterbelts Grain crops with windbreaks Grain crops without shelterbelts under convection Grain crops with shelterbelts under advection

Rn

LE

S

ETP

ETR

ETR ETP

ETR OP

1542 1586 1567 1586

1035 1078 1010 1258

495 496 546 315

650 586 581 898

414 431 404 503

0.64 0.76 0.86 0.56

1.10 1.15 1.08 1.34

1586

1181

412

592

464

0.78

1.24

Heat balance components are expressed in W·m–2 and water balance components are expressed in mm.

landscape structure is the main factor determining the structure of heat balance. If irrigated fields or tree stands are surrounded by the very hot and dry areas, strong spatial differentiation of air temperature is observed. It creates strong horizontal temperature gradients which are a driving force for energy flux flowing from hot air over intensely transpiring surface. Even in humid climate conditions, heat advection over fully developed plant cover causes excessive evapotranspiration. Creation of the proper landscape structure is the best way to counteract this unfavorable process. For example, introducing shelterbelts into a uniform cereal landscape can save as much as 40 mm water during the growing season under advection conditions (Table 3.2). In humid climatic conditions during sunny days, the LE/Rn ratio also reached a very high value for cultivated fields (Figure 3.2B, Turew-alfalfa) amounting to –0.94 (Table 3.1). However, during cloudy days this ratio was not as high in a warm arid climate under irrigation conditions (Table 3.1). Such an important influence on heat balance structure comes from only living plant cover. After maturity and death, plant cover plays a less important role in partition of net radiation into different fluxes. In Cessieres, France on July 16, 1993, heat balance observed for a living sugar beet field (Figure 3.4B) was quite different from that observed for a pea field after maturity (Figure 3.4A). For the sugar beet field, the LE/Rn ratio was 0.93 while for the pea field it was only 0.39. The Bowen ratios were 0.04 and 1.38, respectively (Table 3.1). The above examples support the assumption that the impact of plant cover on heat balance structure is modified by habitat moisture conditions. This impact can easily be seen if longer periods of measurement of the heat balance components are analyzed. Comparison of average value of heat balance components for eight measurement periods in different agroecosystems are shown in Figure 3.5 (Olejnik et al. 2001). The measurement sites and time of investigation cover not only different plants and bare soil but also different weather conditions; measurements were carried out in varied conditions: dry and warm and with and without plants. Also, during the measurement periods different distributions of precipitation were noted and consequently different amounts of habitat moisture. Because of such varied conditions, the measurement results varied significantly (Figure 3.5): Rn was 9 Wm–2 on

0919 ch03 frame Page 40 Tuesday, November 20, 2001 6:29 PM

40

Figure 3.4

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Daily course of heat balance components for peat field (A), and sugar beet field (B) in Cessieres, France on July 16.

September 24, 1997 for bare soil and was 232 Wm–2 on June 12, 1994 for oat; on these days latent heat flux varied from –10 Wm–2 to –203 Wm–2, respectively. The average values of the Bowen ratio varied from –0.04 for period P4 (sugar beet) to 1.0 for period P2 (bare soil) (Figure 3.5). The average value of Rn varied from 50 Wm–2 (P2, bare soil) to 147 Wm–2 (P5, oat), and for the same periods the average latent heat flux varied from –24 Wm–2 (P2) to 133 Wm–2 (P5), which gives ETR of 0.8 mm/day and 4.7mm/day, respectively. For all eight measurement periods, the ratio α = LE/Rn, which describes the percentage of Rn utilized by latent heat

0919 ch03 frame Page 41 Tuesday, November 20, 2001 6:29 PM

P7

P8

Bowen ratio

1.3 1.1 0.9 0.7 0.5 0.3 0.1 -0.1

94 un., June

97 Tur. eet, Sept. ar b

97 ur., . 2), T oil ( Sept

LE/Rn

P6

41

97 un., ), M ne u at (2 J whe 95 un., ), M at (1 June whe

P5

95 un., er, M June flow sun

P4

M oat,

P3

sug

s bare

P2

95 ur., 1), T . oil ( Sept

Figure 3.5

P1

s bare

130 110 90 70 50 30 10 -10

, 95 Tur. lfa, Sept. alfa

Rn - LE

- S [W m-2] -G

MITIGATION OF RADIATION AND HEAT BALANCE STRUCTURE

Comparison of averages of heat balance components and their ratios of eight several-day measurement periods (P1–P8).

flux (energy equivalent of evapotranspiration), varied from 0.49 to 1.04. The highest values of that ratio were observed for the fully developed plant community (sugar beat in September, or oat, wheat, and sunflower in their high plant development stage). On average, the α ratio (LE/Rn) is equal to 0.9 for well-developed plant cover, which means that almost 90% of available energy is utilized for latent heat flux. In cases of bare soil, that ratio is significantly lower. In the first period, P2, the α ratio is equal to 0.5 and rises to 0.78 for bare soil for period P3. In this case for bare soil, that ratio is relatively high because heavy rain occurred during the measurement period; consequently, the soil was very wet, and, although there were no plants, the vaporization was very intense and high latent heat flux was noted.

SEASONAL VALUE OF HEAT BALANCE COMPONENTS FOR SELECTED ECOSYSTEMS AND THE LANDSCAPE To measure seasonal values of heat balance components, it is necessary to carry out long period measurements (over a growing season or whole year); one can use models that can estimate these components on the basis of meteorological and phenological data. The MBC model, described earlier, was used to estimate heat balance components during the growing season for some ecosystems in Turew (Wielkopolska region) in Poland. During the growing season, the values of net radiation in the Turew ecosystems ranged from 1494 to 1883 MJ·m–2 (Table 3.3). The lowest net radiation was observed in the meadow ecosystem, while the highest was in water bodies and forest. Crops of rapeseed, sugar beet, and wheat had practically the same values of seasonal net radiation. The net radiation of meadow was slightly lower than that of cultivated fields. The high net radiation for water and forest was caused by a low reflection of these surfaces (Ryszkowski and Ke˛ dziora 1987, 1995). Rn utilized for air heating

0919 ch03 frame Page 42 Tuesday, November 20, 2001 6:29 PM

42

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Table 3.3

Heat Balance Components (MJm–2) for Different Ecosystems (mean for growing season, from March 21 to the end of October)

Component

Water

Forest

Ecosystem Cultivated Field Winter Sugar Meadow Rape Beets Wheat

Rn LE S G LE/Rn S/Rn S/LE

1883 1585 120 179 0.84 0.06 0.08

1730 1572 121 37 0.88 0.07 0.08

1494 1250 215 29 0.84 0.14 0.17

1551 1163 327 61 0.75 0.21 0.28

1536 1136 339 61 0.74 0.22 0.36

1536 1090 385 61 0.71 0.25 0.45

Bare Soil 1575 866 651 47 0.75 0.41 0.75

(sensible heat flux, S) also ranged significantly for different ecosystems. For example, forest used nearly 5.5 times less energy for air heating than did the bare soil. Energy used for soil heating (soil heat flux G) was the smallest part of net radiation and its average value during the growing season ranged from 29 MJ·m–2 for meadow to 61 MJ·m–2 for cultivated field. However, soil heat flux for bare soil during early spring could reach more than 300 joules per second per square meter, which is equal to the Rn value. The average value of soil heat flux, during the whole growing season, was small because during the first half of the growing season (March to the beginning of August) the soil warms and after this period the soil begins cooling. Consequently, at the beginning of the growing season soil can be considered an energy sink and after that an energy source — daily averages of soil heat flux change from positive to minus: at the beginning of the growing season it is the outgoing flux from the active surface (minus sign in Equation 3.1) and then from the beginning of August it is the incoming flux to the active surface (plus sign in Equation 3.1). Thus, although the seasonal average values of soil heat flux are rather small compared with other components of heat balance, at the beginning and end of the growing season the energy used for soil heating (spring) or cooling (autumn) can be high, equal to, or sometimes even exceeding, the net radiation value. Various ecosystems use net radiation energy in different ways (Table 3.1). The energy used for evapotranspiration (latent heat flux, LE) ranges from 866 MJ·m–2 for bare soil to 1574 MJ·m–2 for forest and 1585 MJ·m–2 for water. Wheat has the lowest evapotranspiration value and water bodies have the highest (LE in Table 3.3) (Ryszkowski and Ke˛ dziora 1987, Ryszkowski and Ke˛ dziora 1993a). The energy values used for evapotranspiration (latent heat flux, LE) also vary greatly for different ecosystems (Table 3.3). Forest uses about 40% more energy for evapotranspiration than does the wheat field, while the wheat field diverts approximately three times the energy to air heating than does the forest (Table 3.3). Therefore, during the growing season, forest or shelterbelts can evaporate about 170 mm more water than can a field of wheat. There are two main reasons for this difference. First, there is a difference in the structure of plant cover. Trees have much longer roots than does wheat, which allows them to use water from deeper layers of the soil. Since trees have greater amounts of available water for their use than cereals

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MITIGATION OF RADIATION AND HEAT BALANCE STRUCTURE

43

do, their leaves also have less stomata resistance. Second, shelterbelts also have greater canopy roughness than does wheat, which, together with higher wind speed in the shelterbelt canopy, results in more intense turbulent exchange over the shelterbelt (Ryszkowski and Ke˛ dziora 1987, Ke˛ dziora et al. 1989). The proportion of energy used for air and soil heating also depends on plant cover. Soil and air heat fluxes depend mainly on temperature gradients existing in the air and soil strata near the active surface. These gradients depend on the amount of solar energy reaching the active surface, which in turn is related to the density and structure of the plant cover (Ke˛ dziora 1999). To illustrate the possibilities for mitigating heat and water balance structure of landscape under different weather conditions, the effect of introducing shelterbelts into agricultural landscape was evaluated (Ryszkowski and Ke˛ dziora 1987, 1995). Introducing shelterbelts into simplified landscapes is one of the best tools for managing heat balance in the landscape. Shelterbelts reduce wind speed and conserve the water supply of the field located between shelterbelts, but they increase little sensible heat flux. However, during strong advection of dry and warm air, irrigated fields can conserve during evapotranspiration as much as 10% more water in comparison with landscape without shelterbelts (Ryszkowski and Ke˛ dziora 1995). Plant cover and landscape structure are the main factors determining the partitioning of net radiation into different internal energy processes of the ecosystem. Bare soil uses only 55% of available energy for evapotranspiration while forest uses 88% (Figure 3.6), but air is heated almost twice as much by bare soil (42% of net radiation) than by alfalfa field (only 20% of net radiation).

LE/Rn, S/LE 0,88

B

0,84

0,76

0,75

0,74

0,8

0,71

0,6 0,55

C 0,30

0,28

MJ•m- 2

Rn

0,4

0,35

0,17

0,2

0,08

0,0

1700

A

1600 1500 RAPE FOREST MEADOW SEED

Figure 3.6

SUGAR BEET

WINTER WHEAT

BARE SOIL

The seasonal value of net radiation, α ratio (LE/Rn) and Bowen ratio (S/Rn) for chosen ecosystems of Wielkopolska region during the growing season (March 21– October 31).

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44

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Again, using the MBC model, the heat balance components for different agricultural landscapes can be calculated. In the input data set of the MBC model, the structure of landscape can be modified and heat balance structure can be estimated for different (modeled or real) landscape structures. Such a procedure creates the possibility of analyzing the heat and water balance structure changes as a function of landscape structure before and after land-use changes. Analysis of the impact of the plant cover and land-use structure on differentiation of heat balance in agricultural landscape by the use of the MBC model shows that the more developed the landscape structure, the smaller the diversification of heat balance structure (Table 3.4). Three different landscape structures are considered. The first landscape, in the Turew region, consisted of 30% forest, 15% meadow, 10% row crops, and 45% cereal. The second was completely agricultural, a uniform landscape consisting of 20% row crops and 80% cereals. The third landscape was mosaic, consisting of 50% forest, 20% meadow, 10% row crops, and 20% cereals. The simplification of landscape structure caused a decrease in seasonal average value of latent heat flux density by 3.73 W·m–2 and an increase in sensible heat by 1.94 W·m–2 (Table 3.3, K2–K1). But changing landscape structure from simple (K2) to mosaic (K3) increased latent heat flux density by 6.2 W·m–2 and decreased sensible heat flux density by 3.31 W·m–2 (Table 3.4 K3–K2). So, the more complex landscape used more energy for evapotranspiration and less remained for air heating. The other results of heat balance components modeling for open agricultural landscape compared with the same landscape with introduced shelterbelts are a good example of such analysis. For this calculation, the alfalfa fields together with bare soil in the neighborhood were chosen. Such a landscape structure creates energy advection (horizontal transfer of energy from one ecosystem to another). The results of the analysis are shown in Figure 3.7. The model results show huge differences between the open landscape and the landscape with shelterbelts. In the open field, evaporation uses 35% more energy than received by net radiation, while the field with shelterbelts uses only 82% of net radiation. In the first case (Figure 3.7A), the ratio LE/Rn is 1.35 and the ratio S/Rn is 0.41, which means the energy deficit for latent heat flux is covered by the sensible heat flux coming from the air to the active surface due to advection. The very intense evapotranspiration (latent heat flux) is caused by the advection, which results in the additional undesirable losses of water from the alfalfa field. After the introduction of shelterbelts into the alfalfa fields, the micrometeorological and plant cover conditions were changed (Figure 3.7B), which in turn altered the heat balance structure of the landscape. The proposed land use structure changes caused the decreased latent heat flux and reversed sensible heat flux. As a result of this change, the S/Rn ratio was –0.13 and the LE/Rn ratio was significantly reduced to –0.82. Such a modification of land-use structure saves water because the latent heat flux was reduced from –105 Wm–2 to –64 Wm–2. Thus, introducing shelterbelts into the agricultural landscape can be an excellent way to conserve water supplies in intensely irrigated fields within agricultural landscapes or areas with low precipitation. The impact of plant cover on heat balance structure is strongly modified by weather conditions — the more humid the conditions, the lower the diversification

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MITIGATION OF RADIATION AND HEAT BALANCE STRUCTURE

Table 3.4

45

Seasonal Average Values of Heat Balance Components under Present and Future Climatic Conditions and Different Landscape Structures

Parameter W· m–2 Latent heat flux density, LE, under present climatic conditions Latent heat flux density, LE, under future climatic conditions Sensible heat flux density, S, under present climatic conditions Sensible heat flux density, S, under present climatic conditions

K1

Landscape K2

K3

49.93 55.44 17.85 15.89

46.20 50.68 19.79 17.94

52.40 58.53 16.48 12.97

Change in Latent Heat Flux Density as a Result of Landscape Structure Change under Present Climatic Conditions K2-K1 –3.73

K3-K1 2.47

K3-K2 6.20

Change in Sensible Heat Flux Density as a Result of Landscape Structure Change under Present Climatic Conditions K2-K1 1.94

K3-K1 –1.37

K3-K2 –3.31

Change in Latent Heat Flux Density as a Result of Landscape Structure Change under Future Climatic Conditions K2-K1 –4.76

K3-K1 3.09

K3-K2 7.85

Change in Sensible Heat Flux Density as a Result of Landscape Structure Change under Future Climatic Conditions K2-K1 2.05

K3-K1 –2.92

K3-K2 –4.97

Change in Latent Heat Flux Density as a Result of Landscape Structure and Climatic Conditions Changes K1p-K1o 5.51

K2p-K1p –4.76

K3p-K1o 8.60

Change in Sensible Heat Flux Density as a Result of Landscape Structure and Climatic Conditions Changes K1p-K1o –1.96

K2p-K1p 2.05

K3p-K1o –4.88

Landscape structure: K1 — 30% forests, 15% meadows, 10% row crops, 45% cereals K2 — 20% row crops, 80% cereals K3 — 50% forests, 20% meadows, 10% row crops, 20% cereals o — present climatic conditions p — future climatic conditions

of heat balance components and structure (Table 3.5). In a dry year, the difference between latent heat of forest and field for the whole growing season is as much as 586 MJ·m–2, while in a wet year this difference reaches only 298 MJ·m–2. The difference between the Bowen ratio (β) of field and forest in a dry year was 0.60,

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46

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

HEAT BALANCE - LANDSCAPE WITHOUT SHELTERBELTS ADVECTION

S

Rn

LE +32 +78

-105

110 G

-5

Rn + LE + S + G = 0 78 - 105 + 32 - 5 = 0

A

HEAT BALANCE - LANDSCAPE WITH SHELTERBELTS ADVECTION

S

Rn

LE

-10 +78

-64

78 -4

B Figure 3.7

G

Rn + LE + S + G = 0 78 - 64 - 10 - 4 = 0 Heat balance component changes after shelterbelt introduction to the agricultural landscape in Wielkopolska region.

while in a wet year it was only 0.16, which means that the differentiation of temperature within landscape is much greater in a dry year than in a wet one and generates very strong local exchange of energy. The differentiation of energy used for evapotranspiration (α) also is much higher in dry years than in wet years. In a dry year, a forest used 85% of Rn for evapotranspiration, while the field used only 58%. In a wet year, the difference is very small; the forest and meadow used nearly 90% of Rn for evapotranspiration and a field used 81% (Table 3.5).

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MITIGATION OF RADIATION AND HEAT BALANCE STRUCTURE

Table 3.5

47

Latent (LE) and Sensible (S) Heat of Chosen Ecosystems in Growing Season (21.03 to 31.10) of Dry, Normal, and Wet Years in Turew and Their Diversification () LE MJ·m–2

Ecosystem

 MJ·m–2

S MJ·m–2

 MJ·m–2

β S/LE

 MJ·m–2

 LE/Rn

 MJ·m–2

Dry Year Meadow Field Field + Shelterbelts Forest

1200 892 998 1478

586

265 638 538 165

473

0.22 0.71 0.54 0.11

0.60

0.80 0.58 0.63 0.85

0.27

Normal Year Meadow Field Field + Shelterbelts Forest

1250 1035 1078 1522

Meadow Field Field + Shelterbelts Forest

1347 1242 1300 1540

487

215 495 458 121

374

0.17 0.48 0.42 0.08

0.40

0.84 0.67 0.68 0.88

0.21

Wet Year

Table 3.6

298

118 288 236 103

185

0.09 0.23 0.18 0.07

0.16

0.90 0.81 0.82 0.89

0.09

Mean Weighted Values of Heat Balance Components and Their Ratios for Wielkopolska Region, 1956–1975

Period

Heat Balance Components W·m–2 Rn –LE –S –G

Summer VI–VIII Warm half-year IV–IX Year I–XII

108 93 45

77 63 39

28 25 6

3 5 0

-LE/Rn 0.71 0.68 0.87

Ratios –S/Rn –G/Rn 0.26 0.27 0.13

0.03 0.05 0

A/LE 0.39 0.41 0.15

It is possible, using the MBC model, to estimate the heat balance components for longer periods and large areas (Ryszkowski and Ke˛ dziora 1995, Olejnik 1996). The calculations must be done in daily or monthly resolution for the whole period under consideration and for all land-use units that exist in the area under investigation. After that, the mean weighted values of all heat balance components can be calculated. Table 3.6 shows the results of such an estimation for the Wielkopolska region. The Rn flux density, average for the entire Wielkopolska region is equal to 108 W·m–2 in summer, 93 W·m–2 in a warm half-year, and 45 W·m–2 in the whole year (Table 3.6). In summer, about 70% of this energy is used for evapotranspiration (latent heat flux) while during the entire year as much as 86% is consumed by this process. Thus, during the three summer months, 225 mm of water can evaporate, and during the entire year 515 mm can evaporate. The annual precipitation in the Wielkopolska region reaches a little more than 600 mm. For air heating only about one quarter of Rn is used in summer and only 6% in the whole year (Table 3.6).

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The seasonal courses of heat balance components differ significantly when a different type of vegetation is taken into consideration (Figure 3.8.). Forest shows a regular course during the growing season and the course of latent heat (LE), sensible heat (S), and soil heat (G) never cross one another. Latent heat flux is greatest during the entire season, and sensible heat flux is greater than soil heat flux. Alfalfa shows a fluctuating type of seasonal course of heat balance components, the result of its two or three harvests during the season. Winter wheat shows intense growth in spring and early summer, while sugar beet grows mainly in summer and autumn. So, in the spring, winter crops have much higher values of latent heat than sensible heat, while row crops have much higher values of latent heat in summer (Figure 3.8). Seasonal courses of heat balance components are under significant influence from the landscape structure. Change in land use can essentially change the course of the fluxes (Figure 3.9A and 3.9B). Simplification of landscape structure (K2–K1 in Figure 3.9) decreases latent heat and increases sensible heat, while developing landscape structure causes the opposite changes. Changes in sensible heat are very small in spring when high moisture of the habitat ensures that simple landscape and composite have the same intense evaporation and the same amount of energy that can be used for air heating. In summer, however, the changes in sensible heat are much greater because the soil water supplies have been used and evapotranspiration from simple and composite landscapes differs significantly. The diversification of heat balance structure for the entire landscape is lower than for particular ecosystems (Table 3.7).

CHANGES IN HEAT BALANCE COMPONENTS UNDER CHANGED CLIMATIC CONDITIONS The MBC model can be applied to the analysis of changes of heat and water balance components due to the global climatic change in a local-catchment scale with the use of quite high resolution (Olejnik 1996, Olejnik et al. 2000). Because the input data set consists partly of meteorological data, it is possible to run the model using new, anticipated climatological data. The results from global circulation models, GCM (2 × CO2), were used as new input data for the MBC model. The increase of temperature (by 4°C) and the increase of precipitation (by 0.4 mm/day) for this part of Europe were assumed (Hulme et al. 1990). The results of this analysis are shown in Figure 3.10. The upper part shows the present conditions of heat and water balance of the Main River catchment in Germany. Scenario I (center section of figure) shows the heat and water balance conditions after climatic change (data from GCM). It is easy to see that the increase in temperature and precipitation will result in a very significant increase in runoff, from 235 mm at present to 306 mm by about 2050. For this scenario, current land-use conditions were assumed as at present no changes were included. Using scenario II, one can try to determine how the land-use structure should be changed to reduce the significant increase of runoff due to climatic changes. By assuming the climatic changes (increased temperature and precipitation) mentioned

-2 Density of the flux (Wm )

-150

-100

-50

0

50

100

150

200

-150

-100

-50

0

50

100

150

Figure 3.8

-2 Density of the flux (Wm )

200

5

3

5

7

7

Winter wheat

3

9

9

11

11

13

13

15

LE

15

G

17

S

G

17

19

21 23 Ten days

21 23 Ten days

LE

Rn

19

S

Rn

-150

-100

-50

0

50

100

150

200

1

-150

-100

-50

0

50

100

150

200

3

3

LE 5

5

Sugar beet

1

Alfalfa

7

7

9

9

G

11

11

S

13

13

G

15

15

17

S

Rn

17

19

19

Rn

21 23 Ten days

LE

21 23 Ten days

Seasonal courses of heat balance components for four chosen ecosystems within Turew. The first ten days are the first ten days of March.

1

1

Forest

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-2

Change of flux density [W m ]

50

20

A

15 10

K3 - K1

5 0 -5 K2 - K1

-10 -15

-2

Change of flux density [W m ]

7

9

11

13

15

17

19

21

23 25 27 29 Ten-days of the year

20 15

K2 - K1

10

B

5 0 -5

K3 - K1

-10 -15 7

Figure 3.9

Table 3.7

9

11

13

15

17

19

21

23 25 27 29 Ten-days of the year

Change in latent (A) and sensible (B) heat flux as a result of landscape changes.

Diversification of Heat Balance Components for Particular Ecosystems and for the Whole Landscape

Parameter

Winter Wheat

Spring Wheat

0.56 0.34

0.62 0.28

Potatoes

Ecosystem Sugar Beet Meadow

Deciduous Forest

Landscape

Bowen Ratio S/LE Average Standard deviation Coefficient of variation

60

45

0.57 0.27 48

0.46 0.25 54

0.42 0.16

0.30 0.12

0.49 0.14

37

42

28

Sensible Heat, S Average Standard deviation Coefficient of variation

–28.4 13.8

–31.4 11.7

–29.4 13.8

–25.2 12.6

–24.4 8.0

–17.9 5.2

–26.1 6.1

49

36

47

50

33

29

23

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Climate (p)

Present condition W.B. 1%

Forest 38%

U.A. 10%

o

T= 8 C

51

Precipitation = 836 ETR = 601

Rn = 54

Agriculture 51%

d-

re

L

an

LE = - 45

tu use struc

Runoff = 235

C = -9

Heat balance

Water balance

Climate (f)

Scenario I

Precipitation = 1007

W.B. 1%

Forest 38%

U.A. 10%

o

T= 12 C

ETR = 701

Rn = 61

Agriculture 51%

re

L

an d-

LE = - 54

tu use struc Land - use

Precipitation = 1007

U.A. 10%

d-

LE = - 60

tu t ru c

use s

Precipitation = 1007

U.A. 13%

o

T= 12 C

LE = - 57

re

L

use s

ETR = 736

Rn = 61

Agriculture Forest 35% 50%

d-

Water balance

Climate (f)

Land - use

an

Runoff = 228

C = -1

Heat balance

Scenario III W.B. 2%

ETR = 779

Rn = 61

Forest 68%

L

an

T= 12oC

re

Agriculture 21%

Water balance

Climate (f)

Scenario II W.B. 1%

Runoff = 306

C = -7

Heat balance

tu truc

C = -4

Heat balance

Runoff = 271 Water balance

Figure 3.10 Mean annual values of meteorological data, heat balance, and water balance components in the Main River catchment in present climatic and land-use conditions as well as future conditions (scenarios I, II, and III). U.A. = urban areas; W.B. = water bodies.

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Change of heat flux density [W m -2]

20 15

LE

10 5 0 S

-5 -10 -15 -20 -25 1

3

5

7

9 11

13

15

17

19

21

23

Number of ten-day period Figure 3.11 Change in latent (LE) and sensible (S) heat as a result of climate and land-use structure changes, K3p–K1o.

above, it is still possible to keep the runoff value at the current level, but the land use structure should be significantly changed. The total forest area should be increased to more than 68% in the whole catchment — theoretically possible but unrealistic in practice. The more realistic future land use conditions were assumed in scenario III (in Figure 3.10). Decreased arable lands and increased forest, water bodies, and urban areas were assumed on the basis of reports on future land use in the European Community. Such changes in land use will significantly decrease runoff from that of scenario I without assuming land-use changes (from 306 mm of scenario I to 271 mm of scenario III). This analysis shows the very significant influence of land-use conditions on heat and water balance. One can hope the MBC model will be a very helpful tool for forecasting water and energy conditions under both new climatic and land-use conditions. As mentioned previously in this chapter, the MBC model is based on the Bowen ratio parameterization. It is possible, using the graphical procedures of the model, to show the areal distribution of the heat balance components. The use of such maps should be very helpful for land-use managers for making decisions about future land use. In the Main catchment there are areas where land use can be modified to increase the areal evaportranspiration, which can significantly decrease the high runoff in the future. Synergetic impact of land use and climatic change on latent and sensible changes is significant (Figure 3.11). In the same period of growing season, these changes can be as great as 15 to 20 MJ·m–2. It is equal to more than 10% of typical daily net radiation.

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There are no special limits in resolution increase for the MBC model. The only one is the resolution of the available land-use data. Because of this, we hope that the MBC model can find application in decision making for new land-use structure on the catchment but also on the local scale due to socioeconomic and climatic changes. As was shown, the solar energy partition, the amount of energy fluxes, and the mass exchange between the Earth’s surface and the atmosphere strongly depend on plant cover type and its condition. Habitat moisture and meteorological conditions also have very important influences on heat balance structure. Better understanding of all the processes of energy and water exchange in the environment, as well as of the factors that influence these processes, creates the possibility of modeling them. Using appropriate models, we can estimate the changes in heat and water balance structures with respect to land use or potential climatic changes. This gives us a new tool to predict the potential environmental changes due to expected climatic and land use changes. Knowledge of such potential changes gives us the opportunity to take action and to minimize the effects of negative environmental changes.

REFERENCES Arya S.P. (1988) Introduction to Micrometeorology. Academic Press, San Diego, 305 pp. Beljaars A.C., Holtslag A.A.M. (1991) Flux parameterization over land surfaces for atmospheric models. J. Appl. Meteor. 3: 327–341. Field C., Berry J.A., Mooney H.A. (1982) A portable system for measuring carbon dioxide and water vapor exchange of leaves. Plant Cell Env. 5: 179–186. Freedman B. (1992) Environmental Ecology. Academic Press, New York, 247 pp. Gurney R.J. (1988) Satellite estimates of evaporation from vegetation. In Climate — Vegetation Interactions. Ed., Gurney R.J., Kluwer Academic Publishers, Dordrecht, 307 pp. Holtslag A.A.M., De Bruin H.A.R. (1988) Applied modeling of the night time surface energy balance over land. J. Appl. Meteor. 27: 659–704. Hulme M., Wigley T.M.L., Jones P.D. (1990) Limitations of climate scenarios for impact analysis. In Landscape-Ecological Impact of Climatic Change. Eds., Boer M., De Groot R. IOS Press, Amsterdam. Ke˛ dziora A., Olejnik J., Kapus´ cin´ ski J. (1989) Impact of landscape structure on heat and water balance. Ecol. Int. Bull. 17: 1–17. Ke˛ dziora A., Olejnik J. (1996). Heat balance structure in agroecosystems. In Dynamics of an Agricultural Landscape. Eds., Ryszkowski L., French, N., R. Ke˛ dziora A. PWRiL, Pozna n´ , 45–64. Ke˛ dziora A., Tucho l ka S., Kapus´ cin´ ski J., Paszyn´ ski J., Les´ ny J., Olejnik J., Moczko J. (1997) Impact of plant cover on heat and water balance in agricultural landscapes located in humidity gradients. Roczniki Akademii Rolniczej w Poznaniu, 294, 271–301. Ke˛ dziora A. (1999) Foundation of Agrometeorology. PWRiL, Pozna n´ , 364 pp. Ke˛ dziora A., Ryszkowski L. (1999). Does plant cover structure in rural areas modify climate change effects? Geographia Polonica, 72(2): 65–87. Ke˛ dziora A., Olejnik J., Tucho l ka S., Les´ ny J. (2000). Evapotranspiration within Wielkopolska and Cessières landscapes. In L’eau de la cellule au paysage. Ed., Wicherek S. Elsevier Editions, UNESCO, Paris, 93–104.

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Kim J., Verma S. (1990) Components of surface energy balance in a temperate grassland ecosystem. Boundary Layer Meteorol. 51: 401–417. Kirchner M. (1984) Influence of different land use on some parameters of the energy and water balance. Progress. Biometeorol. 3: 65–74. Kundzewicz Z., Somlody L. (1993) Climatic change impact on water resources — a system view. International Institute for Applied Systems Analysis, working paper, 32 pp. Les´ ny J. (1998) The influence of plant cover on heat balance structure. Ph.D. dissertation, Library of Agricultural University of Poznan´ , 150 pp. McNaughton K.G., Spriggs W.T. (1985) A mixed-layer model for regional evaporation. BLM 34: 243–262. Molga M. (1986) Agricultural Meteorology. PWRiL, Warszawa, 470 pp. Monteith J.L. (1975) Vegetation and the Atmosphere. Academic Press, London, 278 pp. Olejnik J., Ke˛ dziora A. (1991) A model for heat and water balance estimation and its application to land use and climate variation. Earth Surface Processes Landforms 16: 601–617. Olejnik J. (1996) Catchment scale modeling of heat and water balance structure under present and future climatic conditions. [in Polish] Roczniki Akademii Rolniczej w Poznaniu, Z.268, 125 pp. Olejnik J. (1988) The empirical method of estimating of mean daily and mean ten-day values of latent and sensible-heat near the ground. J. Appl. Meteorol. 12: 1358–1369. Olejnik J., Eulenstein F., Willms M. (2000) Mesoscale heat and water balance structure under present and future climatic conditions — catchment case study in southern part of Germany. Prace Geograficzne. Uniwersytetu Jagielon´ skiego, Kraków, Z 107, 397–405. Olejnik J., Eulenstein F., Ke˛ dziora A., Werner A. (2001) Evaluation of water balance model using data for bare soil and crop surfaces in Middle Europe. Agric. Forest Meteorol. 106, 105–116. Paszyn´ ski J. (1972) Studies on the heat balance and on evapotranspiration. Geographia Polonica: 22. Rosenberg N.J. (1974) Microclimate: The Biological Environment. Wiley, New York, 343 pp. Ryszkowski L., Ke˛ dziora A. (1987) Impact of agricultural landscape structure on energy and water cycling. Landscape Ecol. 1: 85–94. Ryszkowski L., Ke˛ dziora A., Olejnik J. (1991) Potential effects of climate and land use changes on the water balance structure in Poland. In Land Use Changes in Europe. Eds., Brouwer F.M., Thomas A.J., Chawick M.J. Kluwer Academic Publishers, Dordrecht. Ryszkowski L., Ke˛ dziora A. (1993a) Agriculture and greenhouse effect [in Polish]. Kosmos 42: 123–149. Ryszkowski L., Ke˛ dziora A. (1993b) Energy control of matter fluxes through land-water ecotones in an agricultural landscape. Hydrobiologia 251: 239–248. Ryszkowski L., Ke˛ dziora A. (1995) Modification of the effects of global climate change by plant cover structure in an agricultural landscape. Geographia Polonica 65: 5–34. Stigliani W.W., Brouwer F.M., Munn R.E., Shaw R.W., Antonovsky M. (1989) Future Environments for Europe: Some Implications of Alternative Development Paths. International Institute for Applied Systems Analysis, 102 pp. Tanner C.B. (1981) Transpiration efficiency of potato. Agron. J. 73: 59–64. Tenhunen J.D., Kabat P. (1999) Integrating Hydrology, Ecosystems Dynamics, and Biogeochemistry in Complex Landscapes, John Wiley & Sons, Chichester, 363 pp. Thom A.S., Oliver H.R. (1977) On Penman’s equation for estimating regional evaporation. Quart. J. Royal Meteorol. Soc. 103: 345–357.

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Valentini R., Baldocci D.D., Tenhunen J.D. (1999) Ecological control on land-surface atmospheric interaction. In Integrating Hydrology, Ecosystems Dynamics, and Biogeochemistry in Complex Landscapes, Eds., Tenhunen J.D. and Kabat P., John Wiley & Sons, Chichester, 177–197. Wegehenkel M. (2000) Test of a modeling system for simulating water balances and plant growth using various different complex approaches. Ecol. Modeling 129(1): 39–64.

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CHAPTER

4

Water Balance in Agricultural Landscape and Options for Its Management by Change in Plant Cover Structure of Landscape Andrzej Ke˛dziora and Janusz Olejnik

CONTENTS Introduction..............................................................................................................58 General Water Balance ............................................................................................60 Water Balance of Agricultural Landscape ..............................................................64 Structure of Water Balance......................................................................................68 Precipitation ...................................................................................................70 Evapotranspiration..........................................................................................72 Runoff.............................................................................................................73 Factors Determining Water Balance........................................................................75 General Weather and Climatic Conditions ....................................................75 Soil Conditions...............................................................................................81 Plant Cover and Land Use.............................................................................86 Water Management in the Landscape .....................................................................91 Water Deficit in the Landscape .....................................................................91 Improving Water Retention............................................................................96 Controlling Water Balance by Plant Cover Structure ...................................97 Impact of Climate Change on Water Balance ......................................................101 References..............................................................................................................105

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INTRODUCTION Owing to unusually strong hydrogen bonds between molecules, water is one of the most amazing substances in nature. Many of its properties are qualitatively different from those of other substances participating in processes important for biosphere functioning — for example, water has anomalous high temperature at melting and boiling points, one of the highest specific heat and latent heat of evaporation, the highest dielectric constant, and very high dipole momentum. By determining the process of solar energy transformation into organic matter and thereby the conditions of plant growth and development, water determines the level of agricultural production. Thanks to its enormous thermal properties, water controls the thermal status of plants and allows the plant body to store a large amount of thermal energy, which buffers the plant against rapid changes in environmental temperature. Continuous sufficient flux of water flowing through the soil-plantatmosphere system is indispensable for utilizing the potential for the ecosystem to achieve plant growth and high yields. Three scales of water cycle can be distinguished (Figure 4.1): • Global hydrologic cycle (Figure 4.1C), which consists of water exchanged between oceans and continents through atmospheric circulation and river water flow • Local hydrologic cycle (Figure 4.1B, marked by a dashed line), including water exchanged between the land and the atmosphere • Micro-water cycle (Figure 4.1A) which occurs as water circulates between top soil layers and near-surface layers of the atmosphere within plant communities

The last cycle is very rarely considered, but its role in creating microclimatological conditions of agricultural landscapes is very important. In the presence of a dense

Atmospheric flow

C

Evaporation and precipitation

Surface runoff

Precipitation

Evaporation Transpiration ..... .. ...... .....

A

.....

B

Distillation

absorption Root absorption

Infiltration

Percolation gwl

Subsurface runoff Ocean Figure 4.1

Water circulation. A — micro cycle, B — local cycle, C — global cycle.

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plant cover (for example, meadow or rapeseed field) water evaporating from the soil surface does not pass to the atmosphere but instead condenses on the bottoms of leaves, remaining within the plant cover, which explains why even during dry weather a very humid microclimate can exist inside plant cover. One of the insufficiently recognized problems of formation of water balance is how the structure of plant cover in agricultural landscapes impacts the structure of water balance (Ryszkowski and Ke˛ dziora 1995, Ke˛ dziora 1999, Ke˛ dziora and Ryszkowski 1999, Valentini et al. 1999, Mills 2000). There are many studies on the impact of individual elements and characteristics of landscape on individual components of water balance. But, at the level of landscape, many interactions between processes in the landscape as well as between individual components of the landscape are observed. These phenomena are very poorly recognized because their final effects are not the simple sum of their individual effects (Caswell et al. 1972). The exact recognition of terrestrial hydrologic processes is very important for global circulation models (GCM) because the value of these models strongly depends on parameterization of surface processes of water transport and exchange between Earth and atmosphere (Thomas and Henderson-Sellers 1992, Viterbo and Illari 1994). Studies thus far show that the more developed a landscape structure is, the higher its resistance to many threats occurring in the environment. The evolution of nature brought about very high stability of the Earth’s system, lasting until human civilization started. The water cycling that stabilized during the long geological evolution has been disturbed by recent human action (Zektser and Loaiciga 1993). The environment is subject to very deep drought on the one hand and to flood on the other hand. These climatic disasters are becoming more frequent and less predictable. The global distribution of water resources is irregular. Very rarely is there enough precipitation to ensure soil water moisture favorable for plants during the whole growing season. In Poland and in most countries in Europe, water demands of plants in the growing season very often exceed available water supplies — the precipitation and water retained in the soil. During the summer months, evapotranspiration is higher than precipitation, leading to decreased soil moisture and lowering of the ground water table. Central Europe is rather poor in water resources and increased water demands from the human population and possible climate change brings new challenges in water management to support sustainable development of agriculture. The great challenge that faces humankind is to increase water supplies in the agricultural landscape. The average water deficit in the Wielkopolska region in Poland is equal to about 100 mm (100 l/m2), that is, about 3 km3 for the entire Wielkopolska region (total area of the Wielkopolska region is about 30,000 km2). It is impossible to collect such a huge amount of water in artificial reservoirs. Thus, the technical efforts must be supported by the use of natural processes and mechanisms as well as by proper management of the landscape. Increasing soil and surface water retention, conservation of water by reducing crop evapotranspiration and surface runoff, and increasing water use efficiency are the tools for improving water management in the landscape. The development of alternative strategies of water management in the agricultural landscape is necessary for the future of agriculture in central Europe.

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Table 4.1 Water in the Hydrosphere Water Oceans Glaciers and snow cover Ground water Fresh water Salt water Lakes Fresh water Salt water Soil water Atmospheric water Wetlands Rivers Biological water Total Fresh water

Volume (thousands km3)

Percent of Total Volume

1,338,000.00 24,364.10 23,400.00 10,530.00 12,870.00 176.40 91.00 85.40 16.50 12.90 11.47 2.12 1.12 1,385,984.61 35,029.21

96.5 1.725 1.69 0.76 0.93 0.013 0.007 0.006 0.0012 0.001 0.0008 0.0002 0.0001 100.0 2.5

Percent of Fresh Water 69.6 30.1

0.26

0.05 0.04 0.03 0.006 0.003 100.0

Source: UNESCO 1978.

GENERAL WATER BALANCE The structure of water balance depends mainly on precipitation and temperature. Total world water volume is nearly 1.4 billion km3, but 96.5% of it is gathered in oceans (Table 4.1). Fresh water constitutes only about 2.5%, more than two thirds of which is ice-bound. The most active part of the world’s water is in the atmosphere and soil, constituting only 0.08% of fresh water and 0.002% of the total world water (Baumgartner and Reichel 1975, UNESCO 1978, Lwowich 1979). During a year, 577 km3 evaporates and falls as rain, which means that atmospheric water must circulate more than 40 times during a year because its total volume is equal to about 14 km3. Consequently, atmospheric water plays an important role in energy and mass transporting. The water balances of European countries vary considerably (Table 4.2). The lowest precipitation occurs in Poland, the Czech Republic, and Hungary (a little more than 600 mm). Because of its high evapotranspiration, Hungary’s climatic water balance (precipitation minus evapotranspiration) is the lowest. The ratio of evapotranspiration to precipitation is also highest in Hungary (0.90) and very high in other central European countries (Figure 4.2). In Poland, especially in the Wielkopolska and Kujawy regions, the ratio of evapotranspiration to precipitation is also very high (Figure 4.3). In other European countries, including Spain, the ratio of evapotranspiration to precipitation (calculating for the whole country) does not exceed 0.70. The water supplies can be well characterized by water resources calculated per capita (Figure 4.4). This criterion shows that the most strained water conditions occur in Hungary and the Netherlands. But, if we consider transit water (water from a river that flows through a country but originates elsewhere, such as the Danube in Hungary or Slovakia, or the Rhine in Germany and Netherlands), the worst situation exists in Poland. Poland has the least water supply per capita (1.63 thousand m3). Runoff coefficient (runoff/precipitation) is the lowest in

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Table 4.2 Water Balance of Select Countries in Europe Precipitation Evapotranspiration Runoff P E R=P—E

Country Europe Poland Germany Hungary Czech Republic and Slovakia Netherlands Spain France Russia Finland Sweden Norway

Runoff per capita (103 m3)

E/P

R/P

733 604 725 610 735

415 424 430 519 442

318 180 295 90 293

5.11 0.57 0.43 1.72 0.70 0.30 1.4 (1.91) 0.59 0.41 0.81 (3.81) 0.85 0.15 1.9 (4.73) 0.60 0.40

676 636 965 620 549 664 1343

427 380 541 410 234 233 182

249 255 424 210 315 431 1160

0.78 (6.86) 0.63 0.37 3.88 0.60 0.40 4.57 0.56 0.44 6.23 0.66 0.34 22.5 0.43 0.57 24.1 0.35 0.65 96.9 0.14 0.86

Figures in parentheses relate to the case when transit water is included, the Danube in Hungary, the Czech Republic, and Slovakia, and the Rhine in Germany and the Netherlands. Source: Lwowicz 1979.

1.00 0.90 0.80

Ratio E/P

0.70 0.60 0.50 0.40 0.30 0.20 0.10 0.00 H

C

P

S

N

Sp

G

F

Fi

I

N

Country Figure 4.2

Ratio of real evapotranspiration to precipitation (E/P) for select countries in Europe. H — Hungary, C — Czech Republic, P — Poland, S — Slovakia, N — the Netherlands, Sp — Spain, G — Germany, F — France, Fi — Finland, I — Italy, N — Norway.

Hungary (Table 4.1). In Poland it is lower than 30%, but in some regions, especially in the Wielkopolska, the runoff coefficient is lower than 15%. So, the Great Hungarian Plain and Great Poland Plain suffer from water deficits much more frequently than any other region in Europe (Kleczkowski 1991). An especially high risk of drought occurs in the central Wielkopolska and Kujawy regions (Figure 4.5). The

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Figure 4.3

Ratio of real evapotranspiration to precipitation (E/P) in Poland.

Water resources [103 m3/per capita]

25

Without inflow Including inflow

20 15 10 5 0 P

C

H

G

I

Sp

F

N

Fi

Country Figure 4.4

Water resources per capita [103 ·m3]. P — Poland, C — Czech Republic, H — Hungary, G — Germany, I — Italy, Sp — Spain, F — France, N — the Netherlands, F — Finland.

increase of 10% in the area subject to drought will reduce the Warta River flow the following year by 5.5 m3/s, that is, about 4% of the average flow in the years without drought (Figure 4.6). Another unfavorable phenomenon for agriculture is the increasing variation of precipitation from year to year. Normally, annual distribution of precipitation is favorable for vegetation in Poland. Abundant precipitation occurs in summer, but because of very high evapotranspiration it is not enough to cover water needs of plants (Figure 4.7).

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Figure 4.5

63

Map of drought risk in Wielkopolska. Class 1 — lowest risk, class 7 — highest risk.

Average annual flow of Warta River [m3 s-1]

160 140 120 100 80 60

y = -0.5222x + 137.54

40

R2 = 0.5622 20 0

0

10

20

30

40

50

60

70

80

90

100

Percentage of total region area that suffered from drought during the previous year Figure 4.6

Dependence of annual flow of Warta River on percentage of total area impacted by drought during the previous year.

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Amount of water [mm]

120

ETP

100

E 80

P

60 40 20 0 J

F

M

A

M

J

J

A

S

O

N

D

Month Figure 4.7

Annual course of precipitation (P), potential evapotranspiration (ETP), and real evapotranspiration (E), the Wielkopolska, 1951–1995.

All circumstances mentioned above show that water conditions in the agricultural landscape of Poland, as well as in all of Central Europe, require very wise and economical water management, which can be executed only when the factors determining components of water balance are well recognized, thus allowing scientists, decision makers, local government officials, and farmers to construct a proper strategy for sustainable development of rural areas.

WATER BALANCE OF AGRICULTURAL LANDSCAPE Water serves three basic functions in nature: • It is the building material of living organisms. • It is the medium transporting materials in the environment (chemical substances in soil and plants, dissolved and suspended material in waters, soil, and rock materials in erosion processes). • It facilitates energy transport (as sensible and latent heat) by oceanic and atmospheric circulation.

The energy needed to evaporate a 1-mm water layer from 1 m2 of water, that is, 1 kg water, is enough to heat a 10-cm water layer by 6°C and a 33-m high atmospheric layer by as much as 60°C (Figure 4.8). This example shows how important processes of water phase transformation are for controlling thermal conditions of the landscape. Water exists in three phases — solid, liquid, and vapor. Continuous transformation of water from one phase to another is the main mechanism for accumulating or releasing a large amount of solar energy by ecosystems at the landscape scale, and for distribution of solar energy all over the Earth at the global scale.

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65

∆t = 60°C

1 mm 1m Figure 4.8

10 cm

33 m

Latent heat of evaporation: 2 450 000 J kg-1

∆t = 6°C 1m 1m

1m

Effect of applying the same amount of energy for evaporation, water heating, and air heating.

The strong linkage between energy flow through the landscape and matter cycling within environment exists. The energy flux is the “driving force” for matter cycling. The maintenance of steady (within limits) flux of energy and matter is needed to ensure the stability of a system. The most important task is to ensure proper water conditions in the landscape because of the multifunctional role of water mentioned above. Any processes, natural or caused by human activity, that disturb the process of energy flow and water cycling could have substantial effects on landscape functioning and could create serious threats for sustainable development of the agricultural landscape. The worsening of water conditions in rural areas has been observed for several decades. Increasing water deficits, decreasing soil retention ability in the face of growing water demands are the main threats to agricultural development in central Europe. The following causes of this situation must be taken into consideration: • Changes of natural climatic conditions • Changes in land use and landscape structure leading to simplification of landscape structure • Human activity in water management incompatible with fundamental rules of energy flow and water cycling

The broad studies carried out during the second half of the 20th century showed that climatic conditions (precipitation and temperature) generally changed too little to cause the worsening water conditions in Poland (Lambor 1953, Pas l awski 1992, Ke˛ dziora 1999). However, an unfavorable phenomenon has been observed recently — the increasing amplitude of precipitation variation. The periods of high precipitation causing erosion problems alternating with drought periods appear more frequently. In the period 1961–1980 in the Kujawy region, there were 14 periods of drought lasting from 30 to 60 days (Konopko 1985). Evapotranspiration, the outgoing component

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1.0 0.8 0.6

0.4 0.2

1750 Figure 4.9

1850

1950

Year

Change in ratio of meadows and pastures to arable lands in the Wielkopolska.

of water balance, as well as wind speed and water saturation deficit, did not change sufficiently to explain the worsening water condition (Gutry-Korycka 1978). Observations of ground water level show that hydrogeological conditions did not change significantly either (Wójcik 1998). A deep variation in the depth of ground water level occurred, but no trend has been observed in the agricultural landscape. Depletion of ground water level is observed only in the places where very deep transformations of land surface had occurred, for example, brown coal mines or gravel excavations. The last millennium was a period of increasing transformation of the environment in central Europe. At the beginning of the period in the Wielkopolska region, the ground water level was about 1 m lower than it is today mainly because of high evapotranspiration of forests, which covered three quarters of the area (Czubin´ ski 1947). Precipitation was the same as today (Kaniecki 1991). The rate of land transformation increased in the 15th century as colonization increased. At the end of the 14th century, forests covered more than 50% of the total country area, while arable land constituted only 18% of the total area. At the end of the 16th century, forested area decreased to 41%, to 31% at the end of the 18th century, and to 21% just before World War I (Miklaszewski 1928, B l aszczyk 1974). Cleared areas were converted to arable land. Also, pastures and meadows were very quickly converted to arable land. In 1750, the area of grassland was equal to arable land area, in 1850 it dropped to half that of arable land, and in 1950 the grassland area was five times smaller than the area of arable land (Figure 4.9). Decreasing water retention in the environment, accelerated runoff, and decreasing precipitation are the main negative results of landuse changes, especially deforestation. Increasing forestation by 1% increases annual precipitation by 2 to 18 mm (Bac 1968) and decreases runoff (Dubrowicz 1956). After glacier regression, the area that is now Poland was full of many lakes, ponds, and wetlands. Since the human economy started its intensive development

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67

Number of ponds

1000

500

1790 1800

Figure 4.10

1830 1850

1890 1900

1930 1950

1960 2000

Year

Disappearance of water millponds in the south Wielkopolska region.

in the Middle Ages, people have made many mistakes in water management. They began to regulate riverbanks, to straighten streams, and to drain wetlands (Kowalewski 1988, Mathias and Moyle 1992). These activities led to increased river current speed and cutting into the bed, as well as depleted water content in the environment, especially in soils. Many of these activities were done well from the engineering point of view but were completely wrong from the ecological point of view. They provided new land for agriculture, but they increased the amount of water quickly removed from the landscape, destroying many small ponds and degrading soil (Dembin´ ski 1956, Kosturkiewicz and Ke˛ dziora 1995, Ryszkowski and Ke˛ dziora 1996a). Aridification of soil cover increases organic matter decomposition and decreases the soil’s ability to retain water. The introduction of new agricultural technology, especially mechanization, accelerates the disappearance of many postglacial midfield ponds, ditches, and other small meadow strips and wetlands. The use of electric mills instead of water mills almost totally removed small millponds (Go l aski 1988). Of 1208 water mills located in the Wielkopolska region in an area of 15,000 km2 in 1790, only 70 remained in 1960 (Figure 4.10). Thus, land-use changes and errors in water management must be regarded as the main causes of the present water conditions, which are unfavorable for agriculture. This unfortunate landscape management brought about simplified plant cover structure and decreased the total amount of water in the landscape. This approach was taken mainly because of human ignorance of the interaction among processes of energy flow and water cycling coupled with the aim to increase agricultural production and benefits irrespective of environmental costs.

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STRUCTURE OF WATER BALANCE There are three water fluxes (solid, liquid and vapor) entering and leaving the system under consideration. For estimation of water balance, the incoming fluxes are denoted as positive while the outgoing ones are marked as negative. A set of all these fluxes and water content changes in the system is called the water balance equation. The importance of the individual fluxes depends on the time and space scale in which the water balance is estimated. With a shorter period and smaller area, more fluxes and water content changes must be taken into consideration (Gilvear et al. 1993). Going from a field and daily scale to a global and long-term scale, one can exclude more and more components of the water balance equation. On the field scale and for a short period (one or a few days) the water balance equation for soil layers is written as follows: P + E + HS + H G + D + ∆R S + ∆R G + ∆R1 = 0 where P is precipitation (positive), E is evapotranspiration (negative) or condensation (positive), HS is surface runoff (if surface inflow is higher than surface outflow, the Hs is positive; otherwise it is negative), Hg is subsurface inflow or outflow (including lateral flow), D is percolation to the ground water (negative) or capillary upward flow (positive), ∆RS is change of surface water retention, ∆RG is change of soil water retention, and ∆RI is change of plant cover water retention (change of interception). Lengthening the time scale to a month or longer, we can neglect the change of plant cover retention, ∆RI, and increasing the scale to a catchment, the water balance equation can be expressed as follows: P + E + HS + H G + ∆R S + ∆R G = 0 Increasing the time scale to a decade or more (if neither turning to wetlands nor desertification is observed), we can neglect the change of water retention and write the equation of catchment water balance as follows: P+E+H=0 Finally, for the earth surface the water balance equation is the following: P+E=0 The structure of the catchment water balance depends mainly on: • Variability and time distribution of precipitation, the parameter which is discrete in time and space • Physiographic characteristics of catchment (slope, relief, soil cover) • Density and type of plant cover and its development stage • Land use

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69

Boundary of hydrological catchment

Boundary of topographic catchment

r

able laye

Imperme

Figure 4.11

Incompatibility of hydrological and topographic catchment and its impact on ground water outflow.

The size of catchment has significant impact on the accuracy of the water balance estimation. In the case of small catchment, the incompatibility of topographic catchment and hydrological catchment can introduce an essential error in estimating water balance. If arrangement of the permeable and impermeable layers is such that a part of subsurface water runoff can flow out of catchment (Figure 4.11) the evapotranspiration calculated as the difference between precipitation and outflow measured at point A can be overestimated. As the part of catchment from which water flows increases, the error increases. This problem disappeared at the landscape level. At the landscape level, the following four components of water balance must be taken into consideration: precipitation, evapotranspiration, runoff, and soil moisture changes. The last component disappears when a long period is analyzed. One must keep in mind that processes and fluxes important at a lower level of environmental organization form the higher system and can become less important at the level of this higher system, but they are also controlled by mechanisms occurring at this higher level of environmental organization (Tansley 1935, Allen and Starr 1982, O’Neill et al. 1986). For example, water vapor fluxes originating at the level of individual ecosystems depended on microclimatic conditions of the active surface to create the total water vapor flux outgoing from the landscape to the atmosphere. But they are controlled by meteorological conditions of the landscape, which determine the intensity of energy and matter exchange in the atmospheric boundary layer. Similarly, the process of heat advection is very important at the field or ecosystem levels, much less important at the landscape level, and can be negligible at the regional level.

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Table 4.3 Average Monthly Precipitation (mm) in Different Periods in Turew, Wielkopolska Month January February March April May June July August September October November December Growing season Year

1881–1930

1921–1970

Period 1951–1970

1971–1985

1881–1995

39 28 36 43 55 53 86 70 53 39 41 38

38 36 33 42 59 70 76 74 52 50 42 38

40 37 37 44 68 69 84 78 50 48 50 50

43 33 38 46 48 68 83 68 43 41 42 37

39 32 35 43 56 62 82 71 51 43 42 38

410 581

434 610

453 655

410 590

410 594

Precipitation Precipitation is a vital water flux entering the landscape and largely determining the water balance structure. Annual distribution and intensity of precipitation are factors determining conditions of plant production and the quantity of annual runoff. Precipitation is the only component of water balance not under human control at the landscape level. All other components are subject to human activity. The average annual precipitation of the Wielkopolska region ranges from about 580 mm to 650 mm (Table 4.3). The average value of annual precipitation for a period of 100 years is 594 mm (Pas l awski 1990). The average amount of rainfall in the growing season (from the third 10-day period of March to the end of October) varies between 400 and 450 mm. In comparison with other regions of Poland, the Wielkopolska region has one of the lowest amounts of precipitation. However, the distribution of precipitation over the entire year is favorable for agriculture. The amount of summer precipitation (May to August) is 271 mm, or 46% of annual precipitation. Both 24-h and monthly rainfall distribution fit a gamma distribution, as can be seen in Figures 4.12 and 4.13. The density function of such a distribution, f(x), is given by the following equation (Ke˛ dziora 1996b): f (x) =

λk ⋅ x k –1 ⋅ e − kx Γ( k )

where k and λ are parameters of gamma distribution and Γ(k) is the gamma function. The specific equations for daily and monthly precipitation are presented in Figures 4.12 and 4.13.

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71

a -0.23

f(x) = 0.2866 ⋅ x

0.3

⋅e

-0.25 ⋅ x

F(9.6) =0.9 0.9

density function f(x)

f(x)

0.8 F(x) 0.2

0.7 0.6 F(2.2) = 0.5 0.5 0.4

0.1 0.3 0.2 F(0.4) = 0.1 0.1

4

8

12

16

20

24

28

24-h precipitation Figure 4.12

Probability density function f(x) and cumulative distribution F(x) of 24-h precipitation in the growing season (March 21–October 31) in the Wielkopolska region, Poland. a — diagram of distribution.

The median 24-h rainfall distribution is 2.2 mm, and there is only a 10% probability that the 24-h rainfall will exceed 9.6 mm or be less than 0.4 mm. The median of the average monthly rainfall distribution is 35 mm. There is a 10% probability that the monthly amount of rainfall will be less than 10 mm or more than 85 mm. Comparing the latter amount with the average monthly potential evapotranspiration (Table 4.4) shows that irrigation is necessary in the summer months in the Wielkopolska region. On average, for the growing seasons of 1978–1985, about 65% of the days were rainy days, while during the 1920–1970 period the average number of rainy days per month ranged from 10 in September to 14 in January. The mode of monthly rainfall distribution is 20 mm, and this means that in this region the most frequent monthly rainfall reaches 20 mm. However, a higher amount of rainfall occurs in the summer months, and a lower amount occurs in winter. The structure of landscape has no direct impact on precipitation, but by influencing surface processes it can modify the local water cycling, which can indirectly affect precipitation. Even if landscape structure has no distinct impact on the amount of precipitated water, it has significant impact on the amount of rainfall that reaches the soil surface — the richer the plant cover, the greater the amount of rainfall intercepted by it. This water does not reach the soil surface but primarily evaporates, and thus diminishes the loss of soil water supplies (McCulloch and Robinson 1993).

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Diagram of distribution f(x)

0.9

f(x) = 0.0026 ⋅ x

a

⋅e

-0.043 ⋅ x

F(x)

0.02 0.2

1.0 F(85) = 0.9

Density function

F(35) = 0.5

0.01 0.1

0.5

F(10) = 0.1

0

20

40

60

80

100

120

140

160

180

X

200

monthly precipitation [mm] Figure 4.13

Probability density function f(x) and cumulative distribution F(x) of monthly precipitation in the growing season (March 21–October 31) in the Wielkopolska region, Poland. a — diagram of distribution.

Table 4.4 Average Monthly Potential and Real Evapotranspiration in the Turew Landscape, Poland, 1951–1970 Month January February March April May June July August September Oktober November December JJA Growing season Year

Precipitation P [mm] 39 32 35 43 56 62 82 71 51 43 42 38 215 410 594

Evapotranspiration [mm] Potential ETP Real E 15 17 29 49 85 112 107 91 56 30 18 14 310 540 623

15 17 25 45 67 82 84 71 36 22 17 14 237 416 495

ETP/P

E/P

0.38 0.53 0.83 1.14 1.52 1.81 1.30 1.28 1.10 0.70 0.43 0.37 1.44 1.32 1.05

0.38 0.53 0.71 1.05 1.20 1.32 1.02 1.00 0.71 0.51 0.40 0.37 1.10 1.01 0.83

Evapotranspiration Water evaporation depends on many environmental factors, but mainly on solar energy flux and aerodynamic characteristics of the ground surface and boundary layer of the atmosphere. Seasonal variation of energy flux and meteorological conditions,

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73

f(x) = 0.987•x 3.99•e -1.88x

f(x)

Probability density function

F(x) 1.0

F(4.2)=0.9

Frequency diagram 0.4

0.8

0.3

F(2.41)=0.5

0.2

0.6

0.4

0.1

F(1.23)=0.1 0

Figure 4.14

2

4

0.2

6 ETP [mm 24 hours-1]

Probability density function f(x) and cumulative distribution F(x) of 24-h potential evapotranspiration in the growing season (March 21–October 31), Turew, Wielkopolska.

as well as variation of plant development stage, cause essential diversity of evapotranspiration in space and in time (Penman 1948, Ke˛ dziora 1999). In the agricultural landscape of the Wielkopolska during three summer months (June, July, and August) 237 mm of water can be evaporated, during the warm halfyear (April to September) 416 mm, and during the whole year 495 mm. The annual precipitation in the Wielkopolska region amounts to about 600 mm (Table 4.4), (Ke˛ dziora 1996b). During the warm period, potential evapotranspiration exceeds precipitation. Actual evapotranspiration exceeds precipitation considerably during May and June, but during April and July it exceeds precipitation only slightly. The 24-h amount of potential evapotranspiration shows a gamma distribution (Figure 4.14). The average value for five growing seasons (1981 to 1985), from April to September, was 2.66 mm; however, the mode of this distribution was 2.2 mm. There is only a 10% probability that the 24-h potential evapotranspiration in the agricultural landscape of the Wielkopolska region will exceed a value of 4.2 mm, and a 10% probability that it will be lower than 1.2 mm. During the monthly course of potential evapotranspiration, the maximum value is observed at the end of June and beginning of July when it reaches 110 mm per month, while the lowest value occurs in December or January and falls as low as 14 mm per month (Table 4.4). Runoff The amount of water outgoing from the catchment depends on many factors, of which the most important are intensity and spatial distribution of precipitation, density and structure of plant cover, and slope and hydropedological properties of

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Precipitation and infiltration intensity [mm h-1]

74

5

Precipitation

Precipitation, P = 45mm Infiltration, I = 39mm Runoff, Rs = 6mm 6 Rs = 0.13 = 45 P

4 Runoff

3

2 Instantaneous infiltration

1

5 Figure 4.15

10

15 Hour

Formation of surface runoff.

the soil (Ben-Hur et al. 1995). One of the most important factors is the relation between infiltration rate and intensity of rainfall. Thus, in the case of low infiltration capacity, rainfall intensity exceeding the basic infiltration rate cannot infiltrate the soil surface, and it becomes wholly or partly surface runoff (Figure 4.15). In the case analyzed, the intensity of rainfall during a rainstorm lasting 10 h oscillated between 3 and 6 mm/h. It was higher than the infiltration rate, which changed from 4 mm/h (at the beginning of the rain) to 2.4 mm/h at the end (basic infiltration rate). As a result of such a relation, of the 42 mm of rainfall, only 31 mm of rain infiltrated the soil, and 11 mm formed the surface runoff. Land use and plant cover structure are the other important factors in formation of runoff. The time lapse of landscape reaction on intensity of rainfall is greater in the presence of rich plant cover, and the maximum runoff is reduced in comparison with bare soil (Figure 4.16). On average in the Wielkopolska region, surface runoff accounts for approximately 13 to 20% of rainfall, but sometimes it can reach as much as 50 to 60% (Pas l awski 1990). Such conditions are, of course, unfavorable for agriculture because of soil erosion, especially on sloping, light bare soil surfaces. That part of the rainwater not retained by the soil profile percolates through the soil, and leaches and dislocates a material within the soil profile to the ground water. Thus, water from precipitation that runs over the soil surface or percolates through the soil profile plays a most important role in processes of transporting matter and nutrients in agricultural landscapes. Enriching the landscape with any elements by slowing down the surface runoff (shelterbelts, meadow strips, bushes, and so on) is the best tool for counteracting soil erosion and waste of water during rainstorms. In fact, such landscape elements can convert the unfavorable effects of rainstorms into a favorable process of water accumulation within the landscape.

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Ts

Intensity of runoff

arable land

Ts

forest

Time Figure 4.16

Intensity, timing, and time lapse (Ts) of surface runoff from arable land and from a forest.

FACTORS DETERMINING WATER BALANCE Many factors determine the values of individual water fluxes and water balance components; they can be divided into three groups: • General weather and climatic conditions • Physical and hydraulic features of soil • Plant covers characteristics

Many relations and much feedback exist among individual factors, factors and water balance components, and components themselves. As a result of all these mechanisms and interactions, water balance structure shows very high changeability, in both time and space (Kosturkiewicz et al. 1991, Ke˛ dziora 1994). General Weather and Climatic Conditions The total amount of water coming into the landscape as well as potential and real evapotranspiration mainly depends on climatic conditions, but temporal and spatial variability of these phenomena depend on weather conditions, in addition to plant cover (Ke˛ dziora et al. 1987a,b). The broad experimental investigations carried out by the Agrometeorology Department in different climatic zones allow us to understand how interaction between weather conditions and plant cover affect the

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Table 4.5

Water Balance Components and Their Ratios for Bare Soil and Winter Wheat Field in Different Climatic Zones during the Growing Season

Site

Rn MJ·m–2

P mm

ETP

E

A K T M C Z

1680 1572 1442 1461 1663 2210

119 342 375 355 494 319

942 718 582 582 666 1187

116 314 295 301 357 304

Bare Soil E/P ETP/P 0.98 0.92 0.79 0.85 0.72 0.95

7.94 2.10 1.55 1.64 1.35 3.72

Winter Wheat E/P ETP/P

E/ETP

ETP

E

0.12 0.44 0.51 0.52 0.54 0.26

955 730 592 592 685 1188

336 506 460 466 510 553

2.83 1.48 1.23 1.31 1.03 1.73

8.05 2.13 1.58 1.67 1.39 3.73

E/ETP 0.35 0.69 0.78 0.79 0.74 0.47

A — Alm-Ata (Kazakhstan), K — Kursk (Russia), T — Turew (Poland), M — Müncheberg (Germany), C — Cessieres (France), Z — Zaragoza (Spain). Rn — net radiation, P — precipitation, E — real evapotranspiration, ETP — potential evapotranspiration. Growing season is the period between the day when ascending curve of air temperature crosses 5°C (in spring) and the day when the descending curve of air temperature crosses 5°C (in autumn).

water balance of the landscape. The investigations were conducted in a semi-desert area in Kazakhstan near Alma-Ata, a steep zone near Kursk, Russia, transit climate conditions near Turew, Poland and Müncheberg, Germany, humid zone near Cessieres, France, and arid climatic zone near Zaragoza, Spain (Ke˛ dziora et al. 1994). The solar energy flux is high in the arid climatic zone, but the very high surface temperature causes high-earth long wave radiation, and low concentrations of water vapor in the atmosphere cause low atmospheric reradiation toward the Earth’s surface. Thus net radiation is not as high as in the Mediterranean climate but is higher than in humid climatic zones (Table 4.5). However, this net radiation with a very high-saturation water-vapor deficit causes very high potential evapotranspiration. Low precipitation and low soil water retention lead to low real evapotranspiration. In such conditions, the ratio of ETP/P (potential evapotranspiration to precipitation) is very high, the ratio of E/P (real evapotranspiration to precipitation) is also high, but ratio of E/ETP is small. In a transitional climatic zone or semi-arid zone, potential evapotranspiration is also high but can differ significantly mainly because of temperature and saturation vapor pressure deficit differences as well as length of the growing season. In the continental climate zone (Kursk), summer air temperature is higher than in the arid zone (Zaragoza) where spring and autumn months are much warmer. The growing season in Zaragoza also lasts the whole year, which is much longer than in Kursk where it lasts 7 months. As a result, net radiation in Zaragoza is 40% higher than in Kursk, and ETP is higher by about 25%. In humid climatic conditions (Turew, Müncheberg, Cessieres, Table 4.5) net radiation and potential evapotranspiration are lower but real evapotranspiration is on the same order, with the exception of Zaragoza. In all places studied, the ratio of E/P for wheat fields is above 1.0, but the ratio of E/ETP is less than 1.0. In the case of bare soil, the ratio of E/P reaches a value near 1.0 in arid or semi-arid zones and about 0.80 in humid zones. The ratio of E/ETP is very low in dry conditions and reaches a value of about 0.5 in humid climates in the case of bare soil, and about 0.8 in the case of wheat fields.

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Table 4.6 Latent (LE) and Sensible (S) Heat of Selected Ecosystems in the Growing Season (21.03 to 31.10) of Dry, Normal, and Wet Years in Turew, as Well as Their Diversification () Ecosystem

LE MJ·m–2

 MJ·m–2

S MJ·m–2

 MJ·m–2

 S/LE

 MJ·m–2

 LE/Rn

 MJ·m–2

0.22 0.71 0.54

0.60

0.80 0.58 0.63

0.27

Dry Year Meadow Field Field + Shelterbelts Forest Meadow

1200 892 998

586

1478 1250

265 638 538

473

165 215

0.11 0.17

0.85 0.84

Normal Year Field Field + Shelterbelts Forest Meadow

1035 1078

487

1522 1347

495 458

374

121 118

0.48 0.42

0.40

0.08 0.09

0.67 0.68

0.21

0.88 0.90

Wet Year Field Field + Shelterbelts Forest

1242 1300 1540

298

288 236 103

185

0.23 0.18 0.07

0.16

0.81 0.82

0.09

0.89

On the other hand, evapotranspiration depends on humidity during any individual year (Rosenberg 1974). For example, in the Turew region, in the case of alfalfa, the ratio of real to potential evapotranspiration was 0.74 in the dry year of 1982 and 0.90 in the moderately moist year of 1983. In the moist year of 1984, this ratio was as much as 1.0. The diversity of energy and water fluxes in an agricultural landscape is strongly influenced by general water conditions in any individual year (Table 4.6). In a dry year, the difference in total latent heat flux (energy used for evapotranspiration) between forest (using as much as 1478 MJ · m–2 for evapotranspiration during the growing season) and field (using only 892 MJ·m–2) was very high, reaching as much as 586 MJ·m–2. This amount of energy is enough to evaporate 235 mm of water. During a normal year, this difference is lower by about 100 MJ·m–2, but during a wet year it reaches only half of the value of a dry year. The differences between latent heat flux (LE) of individual landscape elements in wet and dry years were as follows: 62 MJ·m–2 for the forest, 147 MJ·m–2 for the meadow, 350 MJ·m–2 for the field, and 302 MJ·m–2 for the field with shelterbelts. These examples prove the thesis that plant cover is a stabilizing and buffering factor of water cycling in the landscape. For a very rich and permanent plant cover (forest), increased moisture habitat causes increased evapotranspiration only by 25 mm, while for the field, which is covered by plants growing only during a part of the growing season, this increase is as much as 140 mm. But if the field is covered by a shelterbelt network, this increase is only

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120 mm. Thus, higher diversification of landscape structure has higher stability of water cycling and water balance at the landscape level. Also the diversification of efficiency of the solar energy utilized for evapotranspiration is higher in a dry year than in a wet year. In a dry year, forest can use as much as 85% of net radiation for evapotranspiration while the field uses only 58% (Table 4.6). In a wet year, the efficiency of solar energy utilization by forest and field differs only by 9%. The increase of habitat moisture causes the increase of the ratio LE/Rn by 4% in the forest and by 23% in the field. Thus, richer plant cover means higher efficiency of energy utilization even when a water shortage occurs. In the humid climate of the Turew region, heat advection above the plant canopy can be observed quite often. In these cases, plants consume more energy for evapotranspiration than is absorbed as net radiation. Weather conditions have a strong impact on the daily course of evapotranspiration (Figure 4.17). This impact is strongly linked with that of plant cover (discussed Sunny day

0.30

300

EB

Rn

0.25

350

250

0.20

200

0.15

150

0.10

100

ES

0.05

50

0.00

0

EB = 3.4 mm ES = 0.3 mm

-0.05

-50

-0.10

-100 6

-1 Evapotranspiration [mm hour ]

7

8

9

10

11 12

13 14 Hour

15 16

17 18

19 20

Cloudy day

0.40

t = 14.5°C. N = 8.9

0.35

150

B Rn

0.30

100

0.25 50

0.20

EB

0.15 B

0.10

0

0.05 0.00

ES

-0.05 -0.10 6

Figure 4.17

Net radiation [W m-2]

0.35

400

A

t = 17.2°C. N = 2.1

7

8

9

10

11

12

13 14 Hour

-50

EB = 1.5 mm ES = 0.7 mm 15

16

17

18

-2 Net radiation [W m ]

Evapotranspiration [mm hour-1]

0.40

-100 19

20

Daily course of evapotranspiration of sugar beet field (index EB) and stubble field (index ES) during sunny and cloudy days, Cessieres, France.

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79

later in this chapter). During a sunny day (Figure 4.17) a daily course of plant cover evapotranspiration is regular, and its intensity can reach a level as high as 0.35 mm/h in the early afternoon hours. The course of evapotranspiration from bare soil or soil covered by nonactive plant detritus is quite different. The maximum is a few times lower, and it decreases before noon. This difference is because plants can use the water stored in topsoil as well as in the deeper layer of the soil profile. Thus, only solar energy input limits intensity of evapotranspiration. There is no limit in access to water supply. In the case of a field without plants, the quickly growing atmospheric water demands and solar energy input force intensive evaporation but only to the point when water stored in a thin soil surface layer has been evaporated. In humid climatic zones, water is usually stored in the thin soil layer during the nocturnal condensation process. When this water is exhausted, moisture of the soil surface layer decreases, causing the reduction of hydraulic conductivity in this layer, which finally leads to a decrease in or a halt to the evaporation process. In such conditions, condensation is usually observed in late afternoon or early evening. During a cloudy day (Figure 4.17) the daily course of evapotranspiration is irregular, maximum evapotranspiration intensity is low, and differences between a plant-covered field and field without plants are not significant. The impact of solar energy flux on the intensity of evapotranspiration increases simultaneously with increasing plant development stage (Figure 4.18), (Ke˛ dziora et al. 2000). During the days with low solar flux (Rn < 40W·m–2) the differences between evapotranspiration of a field covered by poorly developed plants (plant development stage <0.3) and one with well-developed plant cover (plant development

5

4 3

>160 80-120

Figure 4.18

io iat

ad

>0.8

stage

tr

Plant dev 0.3-0.8 elopment

<40

Ne

<0.3

n.

40-80

0

[W

120-160

1

m -2 ]

2

Rn

Evapotranspiration. E [mm]

6

Impact of plant development stage (f) and net radiation (Rn) on evapotranspiration within an agricultural landscape in the Wielkopolska region. (Site and plant species are not distinguished.)

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LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

6 k3 k1 =

5.5

LE/Rn (bare soil) LE/Rn (irrigated field) k2 = LE/Rn (field, regular moisture)

5

k3 =

4.5

k

LE/Rn (field, regular moisture)

LE/Rn (irrigated field) LE/Rn (bare soil)

k1 = 1.6 exp(-5.0 w1)+1.3; r = 0.9918 k2 = 4.0 exp(-6.0 w1)+1.4; r = 0.9942 k3 = 15.0 exp(-7.2 w1)+2.0; r = 0.9985

4 3.5

W1=P.L/Rn 3 k2 2.5 2

k1

1.5 A

K

Z

T M

C

1 0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

W1 Figure 4.19

Efficiency of solar energy uses for evapotranspiration during the growing season as a result of habitat moisture and climatic conditions. Rn — net radiation [W·m–2], LE — latent heat flux density of evapotranspiration [W·m–2], P — precipitation [mm], L — latent heat of evaporation [2,448,000 J·kg–1]. A — Alma-Ata (Kazakhstan), Z — Zaragoza (Spain), K — Kursk (Russia), T — Turew (Poland), M — Müncheberg (Germany), C — Cessieres (France).

stage >0.8) are very small (first row of blocks at the Figure 4.18). A field uses no more than 70% of available solar energy for evapotranspiration. As the solar energy flux increases, the differences in evapotranspiration between fields with different degrees of plant development as well as the ratio of solar energy used for evapotranspiration also increase. During the days with net radiation about 140 W·m–2, a field with poorly developed plant cover can evaporate about 3 mm, using about 75% of net radiation for evapotranspiration, while a field with well-developed plants can evaporate as much as 4.5 to 5.0 mm, using total available solar energy for evapotranspiration. Thus, more developed plant cover results in a higher degree of energy use for evapotranspiration (efficiency of energy use for evapotranspiration is expressed by the alpha ratio, α = LE/Rn). The second important factor for increasing efficiency of the landscape’s energy use is habitat moisture. This mutual impact of plant cover and habitat moisture is strongly affected by general climatic conditions (Figure 4.19). The ratio of energy needed for evapotranspiration of the total amount of precipitation to energy expressed as net radiation, denoted as index W1, expresses moisture conditions of any site (W1 = P·L/Rn). The value of W1 equal to 0.10 means that for evapotranspiration

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of total precipitation (during a growing season) only 10% of net radiation is needed. This value changes from about 12% in an arid zone to 75% in a humid zone. The least efficient energy use is observed in the case of bare soil. In this case evaporation originates only from a thin surface layer, and it is quickly reduced when that layer dries, so intensity of this process is low. Higher efficiency will be observed for the field with plant cover under regular moisture conditions, but the highest efficiency will occur in the case of irrigated fields. The ratio between individual α ratios, denoted as the k ratio, is a measure of plant cover and habitat moisture impact on increasing of energy use efficiency of the fields and the same of the landscape. Thus, the ratio k1 (Figure 4.19) shows how the ratio α of plant cover under regular moisture will increase in comparison with a bare field; however, the ratio k2 shows how the ratio α increases when the field is irrigated. The impact of plant cover or habitat moisture on efficiency of solar energy use is strongly affected by weather and climatic conditions, and the relationship between ratio k and climatic index W1 is nonlinear (Figure 4.19). For example, in the humid climate of Europe, fields with plant cover use about 40% more solar energy for evapotranspiration than bare soil does (k1 equals 1.40) (Figure 4.19). In an arid zone this ratio is equal to 2 (fields with plant cover use solar energy for evapotranspiration two times more efficiently than bare soil does). The impact of habitat moisture on efficiency of solar energy use is even higher than the impact of plant cover. In humid climatic conditions energy use efficiency amounts to nearly 50% but in arid zones it is as high as 170% (k2 is 1.5 and 2.7, respectively). Simultaneous impact of plant cover and irrigation on efficiency of solar energy use shows a synergistic character. In the humid climate condition of Europe, the ratio k3 is equal to 2.0, which means total impact of plant cover and irrigation is equal to 100% (a little more than the sum of their individual impacts: 40% + 50%), but in arid climates this synergistic effect is as high as 500%, while the sum of separate effects of plant cover and irrigation is much lower (100% + 270%). Irrigated and well-developed plant cover use nearly the same or even more energy for evapotranspiration than that determined by value of net radiation, independent of general climatic conditions. Thus, an agricultural landscape shows a much more stabilized efficiency of solar energy use for evapotranspiration than does any individual element making up that landscape. The importance of landscape structure for creating stable efficient solar energy use and for controlling the structure of water and heat balance is higher when moisture conditions are strained. Soil Conditions From the water-balance point of view, soil plays the role of water reservoir. The amount of water stored in the soil, its availability to plants, and its movement depend on the soil’s structure and mineral composition as well as on its organic matter content. Organic matter can absorb much more water than do mineral components. It also improves soil structure and increases soil water capacity. Very important for the structure of water balance is the presence or absence of a shallow ground water level that can ensure intensive evapotranspiration from almost all ecosystems. As ground water level decreases, fewer and fewer plants can use soil water. Not all

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pF

RAW RAW + HAW = ERU WP

4.2

WC

3.0 2.3 1.8

FC

RAW

0.1 Figure 4.20

0.2

}

HAW

} }

NAW

0.3

0.4 Θ [m3m-3]

Soil water characteristics — pF curve. WP — wilting point, WC — critical moisture point (soil moisture level at which the capillary conductivity is vitally reduced), FC — field capacity, RAW — readily available water, HAW — hardly available water, NAW — nonavailable water, ERU — effective useful water retention.

water stored in the soil is available for plants nor does it all support intensive evapotranspiration. One must keep in mind that soil moisture, which determines the amount of water available for plants, as well as water potential, which expresses the work a plant must do to get water, are both factors. The best water characteristic of soil is the pF curve (Figure 4.20). The water retained in soil between about pF = 2.0 and 3.0 fills medium-sized capillaries. This water is readily available for plants (RAW) and ensures enough efficient capillary flow from the deeper soil layers toward the surface to support intensive evapotranspiration. When the soil moisture is running low (pF higher than 3.0), continuity of capillary water is broken, and evapotranspiration intensity decreases. The amount of water readily available for plants depends mainly on the density of medium-sized pores, which in turn depends on soil structure (Figure 4.21). The highest values of RAW occur in medium-textured, well-structured soils and can reach as much as 130 mm in a soil layer 1 m thick. It is enough to ensure evapotranspiration of a sugar beet field during one summer month. The finetextured but poorly structured soil and coarse-textured soil have very low values of RAW, even below 30–40 mm in a 1-m soil layer (Figure 4.22). The capability for water movement in soil is best characterized by hydraulic conductivity, which in saturated zones mainly depends on soil structure and pore size distribution, but in unsaturated zones rapidly declines as soil moisture decreases (Figure 4.23). Thus, water properties of soil are among the most important factors determining areal variability of evapotranspiration in an agricultural landscape. During periods of no rain, the evaporation from bare fields with light soil and deep ground water will sharply decrease while that from fields with plant cover will remain intensive much longer. This phenomenon is well illustrated by the two examples presented below.

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83

pF 7 3

6

TAW

1 2

5 TAW

RAW WW

4 RAW

3

WC FC

2 1

RAW TAW

0.1

0.2

0.3

0.4 θ [cm3 cm-3] Soil moisture

Figure 4.21

Total (TAW) and readily (RAW) available water for (1) coarse, (2) medium, and (3) fine textured soils.

pF 7 6

Soil symbol G1 G2 G3 G4

5 4

w0 0.199 0.193 0.188 0.172

a 3.55 1.98 2.65 4.27

b 0.418 0.352 0.434 0.365

c 0.0391 0.0053 0.0200 0.0445

3 2 1

0 Figure 4.22

0.1

0.2

-1 w(kg kg )

Water retention curves of light soils of the Turew landscape, Wielkopolska. G1 — loamy sand (topsoil — 4.7% humus), G2 — loamy sand (subsoil), G3 — loamy sand (subsoil — second layer), G4 — sandy loam (dipper profile layer).

If the soil is overgrown with plants, evapotranspiration remains stable if deeper soil layers are moist because plants with well-developed roots can absorb water from even very deep layers. Such a situation is well illustrated by the examples presented

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pF

1

2

2 3

3

4 101

1

B 4

100 10-1 10-2 10-3 10-4 10-5 K[m.24h-1]

Figure 4.23

Hydraulic conductivity of the four soil layers presented in Figure 4.22.

in Figures 4.24 and 4.25. In June the soil under 0.5-m tall alfalfa was still moist as a consequence of the previously abundant spring rainfall. At 0.3 m depth, soil moisture was 0.2 m3 ·m–3, only a little less than field capacity, which for the ploughed layer was 0.24 m3 ·m–3. The surface layer of soil was dry, however, and caused great depletion of water potential, which reached a value of –7000 cmH2O (approximately –7 bars) (see Figure 4.24B). As a result of this situation, a high water potential gradient occurred in the near-surface soil layer, but, simultaneously, hydraulic conductivity decreased (Figures 4.24C and 4.24D). Finally, a small soil water flux existed in the surface layer of the soil. (This flux is calculated as the product of hydraulic conductivity and water potential gradient.) On 29 June, a flux equal to 1 mm per day was observed (Figure 4.24E). It was equal to about 30% of potential evapotranspiration for this day. The flux at a depth of 0.3 to 0.45 m was equal to 3 mm per day, ensuring sufficient water inflow to root surfaces from the moist soil layers, so the evapotranspiration rate remained high. When the soil surface is bare, the rate of evaporation depends mostly on the rate at which water moves up to the soil surface from deeper layers. In August, moisture conditions in the top layer of the bare soil were nearly the same as in June (Figure 4.25), and the soil water flux was about 1 mm per day. As a result, real evaporation for this day was 1.24 mm, only 35% of potential evaporation, which was 3.5 mm. Thus, infiltration, water retention, hydraulic conductivity, and the presence or absence of ground water are factors directly determining water conditions in soil and thus evapotranspiration and surface runoff. But these water parameters depend on soil structure which, in turn, depends on such primary soil characteristics as soil particle distribution (texture), mineralogy composition, organic matter content, climatic

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WATER BALANCE IN AGRICULTURAL LANDSCAPE

θ [cm3 cm-3] 0.1 z [m]

10 100 1000

4 z [m]

z [m]

B

A

C

0.4 0.6

Depth

0.2

Depth

0.2

Depth

dφ/dz

pF

3

2

0.2

85

0.4

K [mm 24 h-1] 10-2

10-1

J [mm 24 h-1]

D

0.2 0.4 0.6

θ[ m3 m-3]

0.4

2

dφ/dz

4

3

0

z [m]

0.6

0.4

K [mm 24h-1]

10-2

10-1

1

100 z [m]

D

Depth

z [m]

1000

0.2 0.4 0.6

0.6

10-3

100

C

0.2

Depth

0.4

10

z [m]

B

0.2

Depth

Depth

ETP = 3.3 mm ETR = 3.2 mm Rn = 114 W m-2 LE = - 90 W m-2 S = - 15 W m-2 G = - 6 W m-2

E

0.2

pF

0.2

A

Depth

4

Water characteristics and water flux in the soil profile of an alfalfa field. A — soil moisture, B — soil water potential (expressed as pF), C — gradient of soil water potential, D — hydraulic conductivity (K), E — water flux (J), φ = 10pF, J = K·dφ/dz, Rn — net radiation, LE — latent heat of evapotranspiration, S — sensible heat, G — soil heat, ETP — potential evapotranspiration, ETR — real evapotranspiration.

z [m]

0.4

3

0.6

0.1

0.2

2

z [m]

Depth

Depth

1

100

z [m]

Figure 4.24

0.4 0.6

0.6

10-3

0.2

0.2

E

J [mm 24h-1] 2

3

ETP = 3.5 mm ETR = 1.0 mm Rn = 110 W m-2 LE = - 29 W m-2

0.4

S = - 45 W m-2 G = - 35 W m-2

Figure 4.25

Water characteristics and water flux in the soil profile of a bare field. A — soil moisture, B — soil water potential (expressed as pF), C — gradient of soil water potential, D — hydraulic conductivity (K), E — water flux (J), φ = 10pF, J = K·dφ/dz, Rn — net radiation, LE — latent heat of evapotranspiration, S — sensible heat, G — soil heat, ETP — potential evapotranspiration, ETR — real evapotranspiration.

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conditions (Richmond 1990). Thus, differentiation of soil cover in an agricultural landscape and the plant cover structure and relief are all factors determining variability of water balance structure in the landscape. Plant Cover and Land Use Plant cover together with land use directly or indirectly influence all components of water balance (Ke˛ dziora et al. 1987a, Gregoire et al. 1992, Magid et al. 1994, Ke˛ dziora and Olejnik 1996, Ke˛ dziora 1999, Olejnik et al. 2001). Ecosystem or landscape features such as type of vegetation, plant height, density of plant cover, and plant development stage affect individual components in different ways, but the final effect depends on the scale for which the problem is considered (Ke˛ dziora et al. 1992, Ke˛ dziora 1999). Precipitation is insensitive to changes of a forested area at the local scale, but it increases with increased percentage of forest at the regional scale (Bac 1968). In the Polish lowland, an increase of 1% in forestation increases annual precipitation by 5 mm. At a field or ecosystem scale, the total precipitation is insensitive to plant cover, but the amount of water reaching a ground surface depends significantly on plant cover density, best expressed by leaf area index (LAI — the ratio of the area of the top sides of all the leaves in the canopy projected onto a flat surface to the area of the surface under the canopy) (Neal et al. 1993). It is equal to the number of leaves that would be crossed by a vertical line passing through the canopy, on average. Water interception by plant cover changes from a fraction of a millimeter in the case of poor vegetation to as much as more than 10 mm in very dense, old spruce forest (Monteith 1975, Zinke 1967). Annual interception in forest areas reaches as much as 20 to 25% of total precipitation, and it is higher in a coniferous forest than in a deciduous one. However, one must keep in mind that gauged precipitation does not represent the total amount of water recharging ecosystems. In some cases, especially in mountainous areas, water entering ecosystems in the form of fog-drip or dew can constitute a significant part of total water income, up to as much as 20% of precipitation. Oberlander (1956) observed fog-drip under single Douglas spruce trees over a 40-year period in a San Francisco neighborhood. It oscillated between 175 to 425 mm annually during rainless days. The same results were observed in Australia (Costin and Wimbush 1961), in the Belgian Congo (Auberville 1949), and in Hawaii (Gingerich 1999). Of course this phenomenon is more intense on the edge of the forest than inside it, and, consequently, the structure of plant cover within the landscape plays a very important role. The more ecotons in an agricultural landscape, the more water this landscape can gain as fog-drip. Thus, it is much better to introduce many shelterbelts into the landscape than for one forest to have the same total area. In addition to fogdrip, other phenomena, dew and distillation, especially in low, dense plant cover, can sometimes constitute considerable water income. Dew occurs when water vapor flowing from the upper layer of the atmosphere condenses on the cold top surface of plants or bare soil. Distillation occurs when water evaporating from soil surface covered by a dense plant community does not pass to the atmosphere but condenses on leaf bottoms and drops back on the ground. This water income usually reaches about 20 to 50 mm per year, but in some cases, for example in dense meadows, it

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can reach as much as 100 mm. This phenomenon rarely occurs in forest or tree stands. Thus, the mosaic landscape demonstrates some advantages over the uniform one because all the above phenomena can occur (contrary to a uniform landscape) and total water income is higher, due to internal recycling, than in uniform landscape. This compensation mechanism plays a very important role in formation of water regime in an agricultural landscape. Surface runoff is very sensitive to features and changes of plant cover in any scale. In forests or meadows, the topsoil is usually loose and overgrown by plants. High infiltration capacity of such soils and plant resistance to flowing water significantly reduces runoff. Especially in lowlands, runoff from such ecosystems is reduced to a minimum, excluding unusual rainstorms. In these areas, the subsurface outflow is quite high in comparison with surface runoff and is very stable in time. In contrast to this, in row crop fields or even in grain crop fields, and especially in the case of bare soil, the surface runoff is very high. These areas, because of compaction of the topsoil layer by machinery, very often have low infiltration rates, even in light soil. Moreover, the furrows in row crop fields and small grooves in grain crop fields, especially when they are oriented from the top to the foot of a hill, increase water outflow. Thus, surface runoff from the cultivated fields can be observed even in the case of mild precipitation, and it usually exceeds the subsurface runoff. In general, total runoff, as well as its partition into surface and subsurface outflow, depends on many factors, among which plant cover appears to be the most important. Consequently, in an agricultural landscape, the intensity, timing, and structure of runoff change as landscape diversification changes. In a mosaic landscape with a rich shelterbelt network, many meadow strips, and bushes, total runoff as well as the ratio of surface to subsurface outflow is low. As a result, the water outflow from such a landscape is slow and stable and lasts a long time, creating favorable conditions for rebuilding soil water supply on the one hand, and preventing the small streams from drying up on the other, which in turn allows survival of the many animals and plants living in or near those streams. Within uniform agricultural landscape, the runoff develops quickly, lasts a short time, is very intensive, and occurs mainly in the form of surface outflow (Figure 4.16). Such a situation runs counter to improving water conditions in the environment and may bring about serious soil erosion. Therefore, the more diverse a landscape structure is, the better will be its characteristics of runoff and hence the better the water conditions in the environment. Evapotranspiration is the most sensitive component of water balance affected by plant cover. Evaporation from bare soil is determined by the moisture in the thin surface layer of soil, which in turn depends on hydraulic conductivity of the soil, determining the transport of water from deeper, moist soil layers or from ground water to the surface. But hydraulic conductivity in unsaturated zones strongly depends on water moisture. Thus, the evaporation process from bare soil leads to overdrying of the soil surface, and causes reduction. Water conductivity in plants is much higher than hydraulic conductivity of the soil in unsaturated zones. In addition to depending on the atmospheric water demands, evapotranspiration of plant cover depends on root development as well as on their range. Although the soil surface is drying, the evapotranspiration from plant cover can last much longer than that from bare soil if only the deeper parts of soil

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P1

E1

P1=P2, E1>E2, I1>I2, F1>F2, G1>G2 R1
I1

E2 P2

F1

I2 F2 R2

R1 gwl

G2 G1 Figure 4.26

Differences between (1) forest and (2) crop field water balance components. P — precipitation, E — evapotranspiration, I — interception, F — infiltration, R — surface runoff, G — subsurface runoff.

are moist. This effect is more pronounced the taller the plant is and the deeper its root zone. For example, the potential evapotranspiration over the forest canopy is much higher than over the low plant canopy because the forest canopy, thanks to its greater roughness, absorbs much more solar energy than does low plant canopy and because the saturation water vapor pressure deficit and wind speed, as well as water exchange coefficient, over the forest canopy are much greater than they are over the short plant cover. The trees of shelterbelts function as the water pump, intensifying the water cycling in an agricultural landscape (Figure 4.26). When the daily course of potential or real evapotranspiration is examined, the vital importance of the plant factor can be seen (Figure 4.27). The maximum hourly values of real evaporation from bare soil (Figure 4.27B) are lower than the values of potential evapotranspiration (Figure 4.27A), calculated by the Penman method. The hourly rate of real evaporation reached 0.25 mm, while the rate of potential evapotranspiration was as high as 0.43 mm. At the same time, over the plant community the real evapotranspiration rate (Figure 4.27D) was a little higher than the potential rate (Figure 4.27C), reaching 0.38 mm/h. It should be noted that the potential evapotranspiration rate over plants is lower than over bare soil because of the lower saturation deficit and air temperature over the plant canopy as a result of cooling by intensive evapotranspiration. When the seasonal course of evapotranspiration is considered (Figure 4.28) the prevalence of real (A) over potential (B) evapotranspiration can be observed at the beginning of the growing season when soil moisture is high. For example, during the second 10-day period of May, the real evapotranspiration rate was 34 mm while the potential evapotranspiration was only 31 mm. Such a situation can occur only when the soil moisture is not much lower than field capacity and plants are well developed. Finally, as soil moisture decreases and air temperature and saturation deficit increase, real evapotranspiration becomes smaller than potential evapotranspiration.

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89

1

0.5 Evapotranspiration [mm/hour]

1

3

0.4 2

0.3 4

0.2

0.1

4

6

8

10

12

14

16

18

20 Hour

Figure 4.27

Daily courses of evapotranspiration from different surfaces. 1 — bare soil potential evaporation, 2 — bare soil real evaporation, 3 — potential evaportranspiration of alfalfa, 4 — real evapotranspiration of alfalfa.

3 2 35 30 25 20 15

30

10

20

5

10

April Figure 4.28

May

June

July

August

Ten-day precipitation [mm/ten days]

Ten-day evapotranspiration [mm/ten days]

1

September

Seasonal courses of evapotranspiration from meadow and sugar beet field, as well as potential evapotranspiration. 1 — potential, 2 — meadow, 3 — sugar beet, — long-term precipitation, — precipitation in 1998.

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1.5 Forest Meadow

= 1.2 Field Meadow

600

= 0.88

1.2 1.1

500

1.1

1.05

E/P

Evapotranspiration [mm]

1.44

1.0

400 0.7

300 0.5 200

Bare soil

Forest

Meadow Rapeseed Sugar beet

Winter wheat

100 0 Figure 4.29

Evapotranspiration and ratio of evapotranspiration to precipitation (E/P) for main ecosystems of the Turew landscape during the growing season (March 21– October 31).

In the Turew region, no great differences were observed between evapotranspiration rates of different agricultural crops; however, some small differences do exist. They depend mainly on the type of vegetation. Crops that grow throughout the season, such as alfalfa or grass, show a higher total amount of transpired water than do crops with shorter plant growing periods, such as wheat or sugar beet. In the Turew climatic conditions, a forest evaporates 20% more water than a meadow does and 30% more than a field (Figure 4.29). During the growing season, all ecosystems need more water for evapotranspiration than falls as precipitation. Water deficits (evapotranspiration minus precipitation) vary from 5% for a winter wheat field to 44% for a forest. Only bare soil uses less water for evaporation than supplied by precipitation. Forests use about 40% more energy for evapotranspiration than do wheat fields. Forests or shelterbelts can evaporate about 170 mm more water than can a wheat field. There are two main reasons for this difference. First, there is a difference in the structure of plant cover. Trees have much longer roots than wheat, which allow them to absorb water from deeper layers of the soil. In effect, more water is within the reach of the trees’ roots. Since trees have greater amounts of water available for their use than do cereals, tree leaves have smaller stomatal resistance than cereal leaves. Second, shelterbelts also have a greater canopy roughness than does wheat, which, together with a higher wind speed in the shelterbelt canopy, results in more intensive turbulent exchange of water over shelterbelts. The proportion of energy used for air and soil heating also depends on plant cover. Soil and air heat fluxes depend mainly on temperature gradients existing in near-surface air and soil strata, but they also depend on the amount of solar energy

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reaching the soil. The latter is a function of the density and structure of the plant cover. Plant cover and habitat moisture are the main factors determining the partitioning of net radiation into different internal energy processes of the ecosystems, especially under convection conditions. The direction of air advection is determined by wind direction, but the value of energy transported by advection depends on the temperature gradient, which is controlled by plant cover and moisture of the habitat. So, if a dry area surrounds a wet area covered by fully developed plants, advection brings the energy from the dry area to the wet field, enhancing the difference between latent heat flux of dry and wet fields. The diversification of water balance on the level of landscape is smaller than that on the level of the ecosystem. The more mosaic the structure of landscapes, the smaller the difference between water balance structure of the two compared landscapes.

WATER MANAGEMENT IN THE LANDSCAPE For water management in the landscape to be effective it must be based on full recognition of the interrelations between energy flow and water cycling and must consider the following items: • Water deficits or water surplus in the landscape • Possibility of improving water retention • Possibility of using natural mechanisms and processes to improve water use efficiency in the landscape

Water Deficit in the Landscape As was mentioned in the section on water balance of the agriculture landscape, many water management errors and unfavorable land use practices brought about very strained water conditions in many regions around the world. An especially serious problem of worsening water conditions has been observed in the Polish lowlands, where water deficit is a crucial factor limiting agricultural production. Intensive evapotranspiration combined with rather low precipitation usually leads to water shortage, especially during the growing season. However, the indices of evapotranspiration and precipitation do not sufficiently characterize water conditions in an agricultural landscape from the point of view of water demands and supplies. For this purpose, the interrelations between available energy and water also must be analyzed. These interrelations can be characterized by the following two indices: • Real water demand index — RWDI, ratio of real evapotranspiration to precipitation; RDWI = E/P). • Potential water demand index — PWDI, ratio of net radiation to energy needed for evaporation of precipitation. PWDI = Rn/(P·L). Rn is net radiation [J·m–2], P is precipitation [mm], L is latent heat of water evaporation [J·kg–1] (1 mm = 1 kg/m2).

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Table 4.7 Ten-Year Averaged Values of Water Balance Components in Period IV–IV for Seven Ecosystems in an Agricultural Landscape (D. Ch lapowski’s Landscape Park) Ecosystems Winter crop Spring crop Potatoes Sugar beet Perennial crop Coniferous forest Deciduous forest

Rn [W m–2]

LE [W m–2]

P [mm 24h–1]

E [mm 24 h–1]

P-E

RWDI

PWDI

93 94 94 93 92 103 91

65 62 62 65 68 83 72

2.38 2.38 2.38 2.38 2.38 2.38 2.38

2.30 2.20 2.20 2.30 2.38 2.93 2.53

0.08 0.18 0.18 0.09 0.00 –0.55 –0.14

0.97 0.92 0.92 0.96 1.00 1.23 1.06

1.38 1.40 1.39 1.37 1.37 1.52 1.34

Rn — net radiation [W m–2], LE — latent heat flux density [W m–2], P — precipitation [mm], E — real evapotranspiration [mm], RWDI — real water demand index, PWDI — potential water demand index.

Such an approach was used to characterize the water conditions within D. Ch l apowski’s Landscape Park, which is situated in the center of the Wielkopolska region and which is representative of the Polish lowlands. During normal weather conditions, seasonal evapotranspiration of main crops in agricultural landscapes is only a little less than precipitation, for perennial crops it is equal to precipitation, and for forests it exceeds precipitation (Table 4.7 — RWDI). However, potential water demands (PWDI) are greater than precipitation for all ecosystems. These demands exceed precipitation by 30 to 40% which shows that soil water supplies collected during winter play a crucial role in satisfaction of plant cover water needs. During the entire growing season (from March 21 to the end of October), evapotranspiration values varied from 350 mm for bare soil to 600 mm for moist forests. Crop fields showed values from 430 mm (winter wheat) to 470 mm (rapeseed). Meadow evapotranspiration was in the range of 500 mm. But, if only an individual crop growth period is considered, the differences are much greater. During the period of sugar beet growth (from June 10 to the end of October) precipitation normally amounts to 268 mm and can cover water needs (250 mm). But usually during this period soil water supplies are not readily available for plants. Thus, any disturbance of precipitation must unfavorably impact the growth and yield of this crop. Quite a different situation is observed with winter wheat. From the beginning of April to the end of July, winter wheat needs 295 mm of water. Precipitation during this period amounts to only 243 mm, but soil water supply in a 1-m layer is 40 to 80 mm. Consequently, the winter wheat crop rarely suffers from drought compared to sugar beet. If seasonal courses of evapotranspiration and precipitation are analyzed in more detail, a short period with surplus precipitation is observed, especially during summer when rainstorms occur. This water surplus cannot infiltrate the soil and should be collected in local depressions, increasing small landscape retention — one of the cheapest ways to exploit temporary water surplus. Consideration of precipitation and soil water storage makes it possible to determine actual water deficit. The water retained in a 1-m depth soil profile can be calculated by the use of relations presented in Figure 4.30. Variability of precipitation

0.08

0.16

Figure 4.30

RAW/TAW

SL

SCL

L

SiL

0.57

0.54

0.51

0.49

0.47

1.4 - 1.7 1.35-1.7 1.3 -1.7 1.3 - 1.8 1.2-1.8

LS

0.47

1.2-1.8

CL

SiC

C 0.46

0.44

0.40

1.2-1.85 1.15-1.9 1.15-1.9

SiCL

Diminishing of retention class in relation to share of skeleton in soil matrix: c or g by 1 class c and g by 2 classes vc or vg by 3 classes vc and vg by 4 classes

WP

bk,cr

gr

m pr

gr pr m

Dependence of soil moisture on textural classification, bulk density, and soil structure. TAW — total available water = FC – WP, RAW — readily available water, FC — field capacity, WW — wilting point, c — cobble, g — gravely, bk — blocky, cr — crumb, pr — prismatic, m — massive.

0.60

Sand c m f Soil class -3 Bulk density [kg m ] 1.5 - 1.7

Soil moisture, w [kgkg-1]

0.24

FC

structure

bk,cr

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over a long period should also be taken into consideration. The estimation of water balance with respect to normal, dry, very dry, and extremely dry years (Table 4.8) shows that the potential water supply during the growing season (precipitation + soil water retention) varies from 246 mm in an extremely dry year and sandy soil to 525 mm in a normal year and loamy soil. Average evapotranspiration for an entire agricultural landscape is estimated at 415 mm. So a water deficit in an extremely dry year can vary from 69 mm in loamy soil to as much as 169 mm in sandy soil. Also, in a very dry year (precipitation 62% of that in a normal year) water deficit of the entire landscape varies from 29 mm in loamy soil to 129 mm in sandy soil. Even in a dry year there is a water deficit in sandy and loamy sandy soils. Only in a normal year can the water supplies satisfy the water demands of a cultivated field (Table 4.8). The best evaluative characteristic of water conditions in the agricultural landscape is the relation between energy supplies — the driving force of water flux — and water supplies in the landscape. The EWD index (energetic water demands, the ratio of available energy for ecosystems to energy need for evapotranspiration of all available water in the ecosystem, Table 4.8) shows that in the Wielkopolska region, even in a normal year, there is not enough water for utilizing all available energy. In the case of sandy soils, the water deficit reaches as much as 34%. Therefore, in a normal year sandy soil can evaporate 34% more water than is stored in the soil and brought by precipitation. During an extremely dry year, the deficit of water on loamy soil is 78% and on sandy soil is as much as 131%. That means that in a normal year the water shortage on good soils amounts to about 90 mm (525 mm × 0.17; see Table 4.8) and 145 mm on poor soils. In extremely dry years, these values are as much as 260 mm and 320 mm, respectively. These results show that to ensure efficiency of solar energy utilization for plant growth and thereby achieve high yield, additional water supplies must be stored in the agricultural landscape. Winter precipitation and excessively high rainfall during summer should be collected for irrigation during dry periods. The total amount of water that should be stored in the landscape depends on long-term precipitation distribution as well as on economics. The following example demonstrates how to evaluate water deficit in relation to climatic conditions and soil water-retention ability. The calculation results provided for D. Ch l apowski’s Landscape Park, which has a total of 15245 ha agricultural land, show that 17 million m3 of water should be stored in a normal year, 27.4 million m3 in a dry year, 38.7 million m3 in a very dry year, and as much as 44.7 million m3 during an extremely dry year. To cover the water needs of only the two lightest soils (Types A and B) the water storage should be 5.2; 7.6; 10.2, and 11.7 million m3, respectively, in normal, dry, very dry, and extremely dry years. However, if one wants to calculate the average water deficits for a long period (for example, 10 years) the probability of different precipitation patterns should be taken into consideration. Usually in the Wielkopolska region over a 10-year period, the normal year occurs five times, the dry year three times, the very dry year one time, and the extremely dry year one time. Then, taking into consideration only the two lightest soils, 7 million m3 of water should be stored

Sandy soils Loamy sandy soils Sand loamy soils Loamy soils

Sandy soils Loamy sandy soils Sand loamy soils Loamy soils

A B C D

A B C D

88 90 93 95

E W m–2 415 415 415 415

mm 365 365 365 365

1.34 1.31 1.24 1.17

Normal

425 445 485 525

286 306 346 386

1.58 1.53 1.43 1.34

1.99 1.90 1.73 1.59

EWD in a Year Dry Very Dry

359 379 419 459

2.31 2.19 1.97 1.78

Extra Dry

246 266 306 346

226 226 226 226

Very Dry 62% 186 186 186 186

Extra Dry 50% 60 80 120 160

TAW [mm]

10 30 70 110

–56 –36 4 44

–129 –109 –69 –29

–169 –149 –109 –69

35 45 65 80

RAW [mm]

Water Retention

Precipitation + TAW – Evapotranspiration Normal Dry Very Dry Extra Dry

299 299 299 299

Dry 82%

Precipitation [mm] for Year Normal 100%

Precipitation + TAW in Year Normal Dry Very Dry Extra Dry

552 3166 7587 3940

Rn Area [ha]

TAW — total available water = FC – WP, RAW — readily available water = FC – WC, FC — field capacity, WP — wilting point, WC — critical soil moisture, EDW — energetic water demands. EWD = Rn·(number of seconds in the period)/[2448000·(precipitation + TAW)] Example of calculation: the period IV–IX has 183 days; in a normal year, precipitation + TAW for soil A is equal to 425 mm. EWD = 88·183·86400/2448000·425 = 1.337.

Sandy soils Loamy sandy soils Sand loamy soils Loamy soils

A B C D

Soil Type Class Textural Group

Table 4.8 Water Deficits in Arable Land during the Period IV–IX in D. Ch l apowski’s Landscape Park, Wielkopolska

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each year to ensure maximal utilization of landscape agropotential and a high yield from cultivated fields. However, if one wants to ensure not maximal evapotranspiration in dry years but only evapotranspiration at the level of a normal year, the water reserves that must be collected can be substantially reduced. In a dry year, the deficits will occur only in soil types A and B, reaching 1.4 million m3; in very dry and extremely dry years the deficits will be observed in every soil reaching 10.5 and 16.6 million m3, respectively. Taking again into consideration the frequency of different hydrological years, the average annual water deficits will reach 3.1 million m3 of water, but in a very dry year as much as 10 million m3 of water should be available. The last two figures are very important for water management in the agricultural landscape. This calculation means that within D. Chl apowski’s Landscape Park each year 3 million m3 of water should be stored, and the total volume of water stored should be 10 million m3. Thus, in the case of potential as well as real water deficits, economically justified water needs are too great to be stored by technical means (artificial water reservoirs). So, any activities that lead to increased soil water retention as well as a natural means that increase small landscape retention are of fundamental importance for sustainable development of agriculture. This problem is discussed in more detail in the next section. Improving Water Retention The increase of water retention in the landscape may be obtained by increasing the quantity of water infiltrating the soil and by increasing soil capacity for water retention. The first goal can be achieved by keeping a high rate of soil infiltration and percolation in the topsoil layer. Usually, the infiltration rate is lowered either by natural processes like compacting of soil surface by rain or by tillage work that compacts the soil layer situated just beneath the ploughed layer. Applying no-tillage technology restores natural soil structure and channels made by roots are a very efficient means of water transmission in the soil. Reduction of surface runoff rate increases the time water stays in the landscape, thereby allowing more water to infiltrate the soil (Alconada et al. 1993). From this point of view, bare soil of the cultivated field is a landscape element that deteriorates water balance, while a forest is an element that improves it. So, once again, richer plant cover means a higher amount of water coming into the soil. Although the infiltration capacity of the soil surface is very important for improved water storage, the structure of the soil is the most important factor (see earlier section on soil conditions). Well-structured soil has many pores of medium size that enable the soil to retain a maximal water amount (see Figures 4.21 and 4.30) (Ilnicki 1983, Cies´ lin´ ski and Miatkowski 1989, Cies´ lin´ ski 1997). The best way to achieve this goal is to increase the organic matter content of the soil. Organic matter not only can hold more water than mineral soil components hold, but it also is a main factor of soil structure formation. Usually, the soil with a high content of organic matter has an aggregate structure that enables high water retention. The two top layers presented in the Figure 4.22G1 and G2 originated from the same parent material but differ substantially in organic matter content. The G1 layer is 4.7%

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97

organic matter while the G2 layer is only 0.92%. The bulk densities of these soils are similar — 1588 kg·m–3 and 1638 kg·m–3, respectively. The pF curves (water retention curves) are described by the following equations (Ke˛ dziora 1984): 0.316 − w  G1: pF = 3.55   2 + 0.062 

0.418

0.316 − w  G2: pF = 1.98   w + 0.087 

0.352

Using these equations, one can calculate that the water retention at field capacity of these soils is 225 mm and 90 mm, respectively. Assuming, for simplification, a linear relation between organic matter content and water content, the rate of water retention increases 34 mm per 1% of organic matter in a 1-m soil layer, or 10 mm in a ploughed layer. But one must keep in mind that the soil reservoir is a reservoir, collecting water not only one time but automatically after any intensive rain. At the same time it also reduces surface runoff. Assuming increased soil water retention of only 20 mm, an additional 3 million m3 of water can be stored in the Landscape Park. The second possibility of increasing landscape capacity for water storage is building new small modified ponds and restoring degraded ones (Kosturkiewicz 1985, Kosturkiewicz and Ke˛ dziora 1995, Ryszkowski and Ke˛ dziora 1996b). These small ponds play a dual role very important for water cycling: they collect excess spring and drainage water and also intensify water cycling. A small pond might evaporate 24 to 32% more water than can a reservoir 10 times bigger in the same area. Currently in the Wielkopolska region, there are two small mid-field ponds in every one hectare, but there could be as many as 100 per hectare. A small pond not only collects water in its bowl, but it also increases water retention in the soil within its neighborhood. The ratio of water stored in the soil to water stored in the pond depends on pond size; the smaller the pond, the higher the ratio (Figure 4.31). The ratio of water retained in the soil surrounding the pond to the water stored in the pond itself is greatest for ponds located in light soils rather than in heavy soils; in light soils the range of increase in ground water table as a result of elevated water table in the pond is greater than in heavy soil. Increased soil moisture in the pond neighborhood has another positive effect; it reduces wind erosion of soil. Thus, enriching landscape with mid-field ponds leads to increased water storage, improved soil water conditions, and intensified water cycling. As more energy is used for evapotranspiration less energy remains for air heating. So, improving water conditions in the agricultural landscape can improve the efficiency of solar energy use by that landscape (Tolk et al. 1998). Controlling Water Balance by Plant Cover Structure Many results of investigations show that landscape structure is the most important factor determining the environment’s natural resistance against threats (Ryszkowski

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D

increase of soil water retention range of ground water level increase

Figure 4.31

D

S

S

x h

increase of soil water retention range of ground water level increase

Increase of water retention in mid-field pond and in its surrounding soil as a result of elevation of water level in the pond. S — diameter of water surface in the pond, x — increase of water level, h — average depth of water pond, L — diameter of area impacted by increase of water level in the pond, D — distance of pond impact on ground water level. D = xz, z = distance of pond impact on ground water level when water level was elevated by 1 m.

and Ke˛ dziora 1987, Ryszkowski and Ke˛ dziora 1996a). Landscapes with a more mosaic structure have a higher degree of landscape resistance. The best way to improve landscape structure is the introduction of shelterbelts, strips of meadows, and hedges, rebuilding of damaged postglacial ponds, and maintenance of wetlands and riparian ecosystems. The saturation of landscapes by ecotons and biogeochemical barriers is the most efficient tool for controlling energy flow and matter cycling, which is also necessary for sustainable development of agriculture (Ryszkowski Ke˛ dziora 1987, Ryszkowski and Ke˛ dziora 1993, Ke˛ dziora et al. 1995, Ryszkowski et al. 1999). A network of shelterbelts introduced into a uniform agricultural landscape changes substantially the microclimatic conditions in that landscape (Jansz 1959, Jaworski 1962). The reduction of wind speed in particular causes, in turn, changes in the intensity of other processes and phenomena (Figure 4.32). At the distance from a shelterbelt equal to 4 to 12 times longer than the height of its trees (100 to 300 m if the shelterbelt is 25 m high) the wind speed is reduced to 60% of that in an open landscape and potential evapotranspiration is reduced to 75%. Snow cover is thicker in landscapes with shelterbelts. Thus, the amount of water infiltrating the soil is higher in a mosaic landscape than in a uniform one. The role of shelterbelts is especially important when advection of warm air over the cultivated field is observed (Figure 4.33). In such situations, the additional flux of heat inflow over the plant canopy intensifies the process of evapotranspiration. In the Wielkopolska landscape under such conditions, the alfalfa field can evaporate as much as 834 mm during growing season. Of course, in such situations irrigation is needed because the precipitation amounts to only 400 mm during the growing season, and soil water retention reaches 160 mm at the most. Because of the protective impact of the shelterbelt network, evapotranspiration of the fields located between the shelterbelts decreases to 508 mm, and the precipitation deficit can be covered by soil water retention. The shelterbelts work in two ways: as a pump intensifying water flow

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WATER BALANCE IN AGRICULTURAL LANDSCAPE

}

> 16h

}

4 - 8h

99

Precipitation 107%

Precipitation 100%

Wind speed 60%

Wind speed 100%

Potential evapotranspiration 75%

Potential evapotranspiration 100%

h Snow cover 115% (1h)

4h

Snow cover 100%

8h

16h

Distance from shelterbelt expressed in shelterbelt high (h)

Figure 4.32

Impact of shelterbelts on microclimate in an agricultural landscape.

from the soil to the atmosphere and as a mechanical obstacle reducing wind speed in the entire landscape. So, on the one hand, shelterbelts have a positive impact on the water cycle and on the other hand they protect the cultivated field against the drying force of the atmosphere. During the growing season, evapotranspiration of the uniform cereal landscape in Turew amounted to 414 mm, while the potential evapotranspiration was as high as 650 mm. By introducing shelterbelts into the landscape, one can reduce potential evapotranspiration from whole landscape to 586 mm, increasing simultaneously real evapotranspiration by 17 mm (Table 4.9). However, if one were to introduce only mechanical windbreaks, real evapotranspiration would decrease by 10 mm. Under advection conditions, the impact of shelterbelts is sufficient: the potential evapotranspiration is reduced by 35% and real evapotranspiration by 40 mm. This amount is equal to the typical irrigation dose and has essential economical importance. So, it is possible to control the water balance structure by adequate formation of landscape structure. Presently in Turew, with landscape consisting of 30% forest, 15% meadow, 10% row crops, and 45% cereals, the average value of latent heat flux density during the growing season (21.03–31.10) is equal to 49.93 W m–2 (landscape K1 in Table 4.10). Therefore, total evapotranspiration during this period equals 396 mm. Simplifying the landscape structure by removing forest and meadow reduces landscape evapotranspiration by 30 mm (landscape K2) and improving landscape structure by increasing forest and meadow increases evapotranspiration by 20 mm (landscape K3). Generally speaking, the richer and more diversified the landscape structure, the better the water management in the landscape (Gilpin et al. 1992). Two guidelines should be strictly followed: • Keep as much water as possible in the landscape for as long as possible, taking care that it is properly allocated. • Ensure that as much water as possible flows from the soil into the atmosphere via plant transpiration, but not as evaporation from the soil to the atmosphere.

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Water balance of alfalfa field without shelterbelts Advection Precipit.

Evapotransp.

400 834

20 454 P + ETR + H + R = 0

400 - 834 - 20 + 454 = 0

Water balance of alfalfa field with shelterbelts Advection

Precipit.

Evapotransp.

400 508

40

148

P + ETR + H + R = 0 400 - 508 - 40 + 148 = 0 Figure 4.33

Impact of shelterbelts on water balance of alfalfa field under advection.

Table 4.9 Water Balance Components of Different Agricultural Landscapes in the Turew Vicinity in the Growing Season (March 21–October 31) Landscape Cereal monocultures Cereal monocultures with a net of shelterbelts Cereal monocultures with windbreaks Cereal monocultures without shelterbelts under advection Cereal monocultures with shelterbelts under advection

Rn MJ·m–2

LE MJ·m–2

ETP mm

E mm

E/ETP

E/P

1542 1586

1035 1078

650 586

414 431

0.64 0.76

1.10 1.15

1567 1586

1010 1258

581 898

404 503

0.76 0.56

1.08 1.34

1586

1181

592

464

0.78

1.24

Rn — net radiation, LE — latent heat of evapotranspiration, ETP — potential evapotranspiration, E — real evapotranspiration, P — precipitation.

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Table 4.10

101

Seasonal Values of Latent Heat Flux Density and Evapotranspiration under Different Landscape Structure

Parameter –2

Latent heat flux density, LE [W m ] Evapotranspiration in growing season [mm] Change of latent heat flux density, LE as a result of landscape structure change [W m–2] Change of evapotranspiration as a result of landscape structure change [mm]

K1

Landscape K2

K3

49.93 396 K2–K1 –3.73 K2–K1 –30

46.20 366 K3–K1 2.47 K3–K1 20

52.40 416 K3–K2 6.20 K3–K2 50

K1 — 30% forest, 15% meadow, 10% row crop, 45% cereals; K2 — 20% row crop, 80% cereals; K3 — 50% forest, 20% meadow, 10% row crop, 20% cereals.

IMPACT OF CLIMATE CHANGE ON WATER BALANCE Because of the strong link between energy flow and water cycling, the changes of atmospheric chemistry, plant cover, and land use observed recently, leading to transformation of the earth’s energy conditions, have brought about changes in global, regional, and local hydrology (Ryszkowski et al. 1989, Valdés et al. 1994). The result of such changes are generally unknown because of the many feedback mechanisms between climate change and water in the environment (Ryszkowski et al. 1990, Ryszkowski and Ke˛ dziora 1995, Stohlgren 1998). One of the most complicated problems is that of the scale (Milly 1991). There have been many laboratory experiments on reactions of plants to enhanced CO2 concentration, temperature increase, and soil and atmosphere moisture changes (Blasing 1985, Callaway and Currie 1985). But because of the many interactions between environmental factors, and the processes of competition and synergism, the results of these investigations cannot be uncritically applied to the landscape level (Ryszkowski and Ke˛ dziora 1999). Temperature and habitat moisture changes will affect the geographical range of many cultivated crops. Mean annual temperature increase of one degree in mid-latitude northern hemisphere countries would tend to move the thermal limit of cereal crops north by about 150 to 200 km, and raise the altitude limit by about 150 to 200 m (Parry and Swaminathan 1992). But in these countries where precipitation will not increase sufficiently, this positive effect of temperature increase might be reduced by water shortage caused by increased evapotranspiration. On the other hand, the increase of temperature mainly during the winter will unfavorably change the annual pattern of precipitation and evapotranspiration (Jaworski and KrupaMarchlewska 1989). Duration of snow cover will be shortened or may disappear altogether, while evapotranspiration and surface runoff will increase and will change annual distribution (Vehviläinen and Huttunen 1997). For example, in the Wielkopolska, during very warm winters in recent years, evapotranspiration was two to three times higher than during normal years. Such a situation will make impossible the rebuilding of soil water storage lowered during the previous growing season, and the new growing season will begin without water supply in the soil (Manabe and Wetherald 1986, Wilson and Mitchel 1987, Nash and Gleick 1992, Rango and

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van Katwijk 1990). Many parts of the world can suffer from such a situation, including central and eastern Europe (Parry and Swaminathan 1992, Parry 1990). Other phenomena that can exert an influence on water conditions in agriculture are frequency of extreme events such as floods and droughts (Gleick 1992). Increased global temperature will intensify global water circulation, which will in turn increase global precipitation (Jager 1988). But because of the very complex character of global air circulation, nobody is able to say where precipitation will increase and where it will decrease (IPCC 1996). Precipitation will probably continue to increase in regions where it is higher today and decrease in areas that are dry today. Because Poland and Central Europe are located in the transition climatic zone, it is very difficult to determine if precipitation will increase or decrease in this region. The crucial problem for the sustainable development of agricultural landscape is how global climate changes will alter the water balance structure of an agricultural landscape. The answer is even more difficult to determine if the impact of climate changes is linked to changes in land use (Brouwer and Chadwick 1991, Gottschalk and Krasovskaia 1997). Taking into account different possibilities of temperature, precipitation, and forestation changes (Bach 1988), a few scenarios for Poland are possible (Table 4.11). Table 4.11

Scenarios of Probable Climatic and Forestation Changes in Poland as a Result of Doubling of CO2 in the Atmosphere

Scenario

Temperature Change

Precipitation Change

0

Air temperature changes from 0 to –6°C in winter and from 16 to 19°C in summer Increase in air temperature by 2°C in summer and –6°C in winter

Lowest in winter, highest in summer; annual precipitation is equal to 700 mm Increase in precipitation by 0.6 mm/day in spring and by 0.4 mm/day in other period (average 23%) Increase in precipitation by 0.6 mm/day in spring and by 0.4 mm/day in other period (average 23%) Increase in precipitation by 0.6 mm/day in spring and by 0.4 mm/day in other period (average 23%) Decrease in precipitation by 20%

1

2

Increase in air temperature by 2°C in summer and –6°C in winter

3

Increase in air temperature by 2°C in summer and –6°C in winter

4

Increase in air temperature by 2°C in summer and –6°C in winter Increase in air temperature by 2°C in summer and –6°C in winter

5

6

Increase in air temperature by 2°C in summer and –6°C in winter

Decrease in precipitation by 20%

Decrease in precipitation by 20%

Forestation Change 28% in country area

Increase in forest area by 10% of present area Degradation in forest ecosystems in 50% of forest area Total degradation in forest

Increase in forest area by 10% of present area Degradation in forest ecosystems on 50% of forest area Total degradation of forests

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The first scenario is the most optimistic: increased temperature (6°C in winter and 2°C in summer), increased precipitation (about 180 mm per year), and increased area of forest (10% of present area) will result in improvement of the water balance. During plant growth period in the Wielkopolska, evapotranspiration will increase by about 40 mm, but the increase of precipitation will be higher and water deficit will disappear. However, if evapotranspiration during the winter is higher than today, the increase in precipitation will not increase climatic water balance (P-E, Table 4.12). So the annual climatic water balance will increase only slightly (136 – 97 = 39 mm, Table 4.12, part for the whole year). But if the current process of forest degradation is continued in the future, and if the increase of precipitation is accomplished by the decrease of the energy used for evapotranspiration (impoverishment of the forested area), diminishing of forest function of the landscape will occur. This situation will lead to increased winter and annual climatic water balance, and it can give rise to serious threats to the agricultural landscape, especially water erosion. In the case of scenario 4 (Table 4.12) — increased temperature and forested area, but decreased precipitation — new water conditions will cause a serious problem for the existence of agricultural ecosystems. Even with decreased forest evapotranspiration, due to forest degradation (scenario 5), land desiccation will be so high that plant cultivation without irrigation will be impossible. So in this case, the environment will be transformed into steppe, and grasslands will replace the forest ecosystems in the Wielkopolska. In Central Europe, evapotranspiration during the plant growing period usually exceeds precipitation, so plants must use soil water supplies, thus depleting ground water level. Normally during the winter, snow precipitation rebuilds soil water supplies. But if in the future the temperature increases by 6°C, precipitation water will evaporate and the growing season will begin with small supplies of water, causing serious problems for agriculture development (Ke˛ dziora 1991, Ke˛ dziora 1996b). IIASA modeling results cite only Poland, England, and Spain as the European countries in which water scarcity will occur in the 21st century (Niemann 1994). Generally, in the future, even with increased precipitation, the ratio of evapotranspiration to precipitation in summer months can increase. The wise strategy of water management is imperative in the face of increasing demands of irrigation water to sustain the development of agriculture. In such a situation, any activity in the frame of landscape structure leading to increased landscape water retention and increased efficiency of water use are crucial for future sustainable development of the agricultural landscape (Bouwer 1994).

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Table 4.12

Water Balance (mm) in the Wielkopolska (W) and All of Poland (P), According to Scenarios in Table 4.11

Scenario

Region

0

W P W P W P W P W P W P W P

83 84 92 92 85 85 64 65 92 92 85 85 64 65

W P W P W P W P W P W P W P

4 5 6 6 4 5 3 4 6 6 4 5 3 4

4.29 3.68 5.00 5.56 7.00 6.09 7.33 6.60 5.00 5.56 7.00 6.09 7.33 6.60

W P W P W P W P W P W P W P

43 44 49 49 45 45 34 34 49 49 45 45 34 34

0.93 0.86 1.02 1.00 1.00 0.98 1.00 0.98 1.02 1.00 1.00 0.98 1.00 0.98

Rn

LE/Rn

P

E

P-E

E/P

ETP

–17 42 28 83 80 134 183 231 –128 –80 –76 –29 27 68

1.04 0.91 0.94 0.84 0.83 0.75 0.62 0.56 1.40 1.22 1.23 1.08 0.92 0.81

492 455 575 578 523 546 487 462 575 578 523 546 487 462

110 96 194 188 181 175 142 135 194 188 181 175 142 135

112 166 106 152 119 165 158 205 –8 29 5 42 44 82

0.50 0.37 0.65 0.55 0.60 0.51 0.47 0.40 1.04 0.87 0.97 0.81 0.76 0.62

108 98 222 208 210 196 174 162 222 208 210 196 174 162

515 495 644 629 580 566 438 429 644 629 580 566 438 429

97 212 136 240 200 303 342 440 –140 –49 –76 14 66 151

0.84 0.70 0.83 0.72 0.74 0.65 0.56 0.49 1.28 1.08 1.15 0.98 0.87 0.74

600 553 780 745 744 705 624 592 780 745 744 705 624 592

Plant Growth Period (IV–IX)

1 2 3 4 5 6

0.76 0.74 0.76 0.75 0.73 0.72 0.72 0.70 0.76 0.75 0.73 0.72 0.72 0.70

396 444 480 528 480 528 480 528 324 365 324 365 324 365

413 402 452 445 400 394 297 297 452 445 400 394 297 297

Winter Period (X–III) 0 1 2 3 4 5 6

222 262 300 340 300 340 300 340 186 217 186 217 186 217

Whole Year 0 1 2 3 4 5 6

612 707 780 869 780 869 780 869 504 580 506 580 504 580

P — precipitation, E — real evapotranspiration, ETP — potential evapotranspiration, Rn — net radiation [W·m–2].

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CHAPTER

5

Control of Diffuse Pollution by Mid-Field Shelterbelts and Meadow Strips Lech Ryszkowski, Lech Szajdak, Alina Bartoszewicz, · and Irena Zyczyn´ ska-Ba l oniak

CONTENTS Introduction............................................................................................................111 Environment of the Turew Agricultural Landscape..............................................113 Nitrogen Compounds in the Drainage System of the Turew Landscape.............116 Control of Mineral Nitrogen Pollution by Shelterbelts and Meadows ................119 Processing of Mineral Nitrogen in the Biogeochemical Barriers ........................122 Landscape Management Guidelines for Efficient Control of Nitrogen Pollution ...............................................................................................................129 Prospects for Control of the Diffusion Pollution through Management of Landscape Structure.............................................................................................135 References..............................................................................................................139

INTRODUCTION Water quality is one of the fundamental requisites for sustainable development of agriculture, and it constitutes the survival determinant of rich plant and animal assemblages. Interactions among physical, chemical, and biological processes characteristic of a watershed determine discharged water quality; alteration of any one of these processes will affect one or more water quality properties. This fact was recently learned by scientists and the public when growing problems of water contamination were unsuccessfully tackled with only technical measures (water purification plants). Activities aiming at water pollution control in the 1970s and up to the mid-1980s focused on treating urban and industrial sewage effluents — that

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is, on the control of point sources of pollution by construction of water purification plants (Vollenweider 1968). Success was achieved in some reservoirs, such as Lake Constance, but eutrophication problems could not be totally eliminated, and, in addition, such problems started to appear even in water bodies located far away from point sources of pollution (Halberg 1989, Kauppi 1990). As agricultural production intensified, land-use changes caused by agriculture became more apparent. Enlargement of farm sizes was linked to more efficient use of machines, which decreased costs of the cultivation of large fields not segmented by shelterbelts (mid-field rows of trees), open drainage ditches, and other obstacles to fast and powerful agricultural equipment. This trend of agricultural development resulted in homogenizing the countryside structure. For example, in France the average farm size increased from 19 to 28 ha in the period from 1970 to 1990. In the same time span, the average farm size in the U.K. increased from 54 to 68 ha, in West Germany from 13 to 18 ha, and in Belgium from 8 to 15 ha (Stanners and Bourdeau 1995). Consolidation and expansion of cultivated fields led to eradication of field margins, hedges, shelterbelts, small mid-field ponds or wetlands, and other nonproductive elements of the landscape. Thus, for example, 22% of hedgerows in the U.K. were eliminated by the mid-1980s (Mannion 1995). The disappearance rate of wetlands in the European Union, excluding Portugal, has amounted to 0.5% annually since 1973 (Baldock 1990). In Denmark, 27% of small water reservoirs disappeared from 1954 to 1984 (Bülow-Olsen 1988). By intensifying production, farmers interfere with patterns of element cycling in landscapes using fertilizers and pesticides, and they are changing water regimes by drainage or irrigation. Feedback of the agricultural measures of production as well as induced changes in land use brought environmental problems, such as impoverishment of biological diversity or nonpoint (diffuse) water pollution. In the 1980s, it was recognized that control of point sources of pollution could not alone solve the problems of water quality. The water pollution, especially with nitrates, was detected in streams or lakes located far from urban or industrial point sources (Omernik et al. 1981, OECD 1986, Halberg 1989, Ryszkowski 1992). The diffuse water pollution problems were recognized worldwide in the 1990s. Nonpoint water pollution is attributed to human-induced, above-natural-rate inputs of chemical compounds into subsurface and surface water reservoirs. At present, agriculture is undoubtedly the main reason for diffuse pollution problems (OECD 1986, Rekolainen 1989, Kauppi 1990, Ryszkowski 1992, Flaig and Mohr 1996, Johnsson and Hoffmann 1998). High concentrations of nitrates exceeding 50 mg per liter of soil solution were detected in Germany, northern France, eastern England, northwestern Spain, northern Italy, and Austria. Very high nitrate concentrations were detected in Denmark, the Netherlands, and Belgium (Stanners and Bourdeau 1995). So, at the beginning of the 1990s, it appeared that modern intensive agriculture practices were threats to the environment and that the Common Agricultural Policy (CAP) of the European Union should be changed by introduction of more environmentally friendly technologies (Stern 1996). Simultaneous with growing concerns about diffuse pollution were studies showing that permanently vegetated land strips could control inputs of chemicals from cultivated fields to waterbodies (Pauliukevicius 1981, Lowrance et al. 1983, Peterjohn

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and Correll 1984, Pinay and Decamps 1988, Ryszkowski and Bartoszewicz 1989, Muscutt et al. 1993, Hillbricht-Ilkowska et al. 1995, and others). The majority of the studies concerned riparian plant buffer zones and their efficiency for the control of diffuse pollution. A thorough review of the riparian-strip functions for controlling diffuse pollution, both via surface and subsurface fluxes, published by Correll (1997) in proceedings of the 1996 buffer zone symposium, provides a review of studies on various aspects of diffuse pollution control (Haycock et al. 1997). A recent book edited by Thornton et al. (1999) addresses primarily the nonpoint pollution impacts on lakes and reservoirs, stressing the practical aspects of the control. As stated above, most studies concerned protection of surface water reservoirs from diffuse pollution by riparian vegetation strips. Field studies have shown, for example, that nitrates are efficiently removed from shallow ground water passing through the root system of plants in a buffer zone. Mechanisms responsible for that process are still elusive (Correll 1997), but it is generally assumed that the following processes are important: ion exchange capacities of soil, plant uptake, and denitrification. Long-term studies on the function of shelterbelts and stretches of meadows within the Turew agricultural landscape, carried out by the Research Centre for Agricultural and Forest Environment, Polish Academy of Sciences, provided information on control of diffuse pollution in upland parts of drainage areas, which enriched knowledge on control of nonpoint pollution outside riparian zones. Those studies also disclosed some mechanisms for a ground water pollution control, which can be useful for developing a strategy of water resource protection. Review of these studies will be used to evaluate the prospect for diffuse pollution control in agricultural landscapes.

ENVIRONMENT OF THE TUREW AGRICULTURAL LANDSCAPE The Turew landscape (about 17000 ha) has been the object of long-term studies on agricultural landscape ecology (Ryszkowski et al. 1990, 1996), and detailed characteristics of climate, soils, hydrology, and land-use forms can be found in those publications. The landscape is identified by the adjacent village, Turew. The terrain consists of a rolling plain, made up of slightly undulating ground moraine. Differences in elevation do not exceed a few meters. In general, light soils are found on the higher parts of the landscape with favorable infiltration conditions (glossudalfs and hapludalfs). Endoaquolls and medisaprists occur in small depressions. The infiltration rates of upland soils range from a few to several cm·h–1 and can be classified as having moderate or moderately rapid infiltration rates. Thus, the water from rain or snow thaw can easily infiltrate beyond the depth of plant roots and then transport dissolved chemical compounds to ground water; however, in layers below 60 cm (argillic and parent material horizons) infiltration rates are slowed due to higher clay content. The content of organic carbon in the ochric horizon (upper horizon of soil) of upland soils ranges from 0.5 to 0.8%, total nitrogen amounts from 0.05 to 0.08%, and the ratio of C:N changes from 8:1 to 11:1 (Table 5.1). Soil reaction in the ochric and luvic horizons varies generally between 4.5 and 5.5 pHKCL. In deeper parts of the soil profile, soil reaction approaches neutral or slightly alkaline

30.8 ± 3.1 26.9 ± 7.4 37.8 ± 12.6 —

Soil Horizon

Ochric Luvic Argillic Parent material

0.62 ± 0.14 0.21 ± 0.12 n.d. n.d.

Organic C (%) N Total (T) 0.075 ± 0.019 0.025 ± 0.012 n.d. n.d.

3.1 2.7 14.2 11.9

± ± ± ±

1.2 0.9 3.7 3.3

49.2 34.8 95 81.2

± ± ± ±

1.2 0.9 1.7 1.9

CEC mmol (+)·kg–1

CEC — cation exchange capacity; S — sum of bases; BS — percent of saturation with bases n.d. — not determined Source: Bartoszewicz 2000.

Thickness (cm)

Contents of Clay Below 0.002 mm (%)

Means of Physical and Chemical Characteristics of Hapludalfs and Glossudalfs

30.4 24.6 71.7 66.8

S mmol (+)·kg–1

61.8 70.7 75.2 82.3

BS (S:CEC) (%)

114

Table 5.1

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values of pHKCL. The alkaline reaction is caused by the presence of calcium carbonates in the boulder loam. The low values of cation exchange capacities of the soil, as well as small amounts of clay fractions and organic matter, indicate that with fast percolation of water there is intensive leaching of chemical solutes. Thus one can infer that sorption of ammonia ions as well as other cations is rather low in the upper horizons of soils located in the upland parts of the landscape and moderately low in deeper layers. The opposite situation is observed in endoaquolls and medisaprists situated in the depressions of the landscape. These soils are characterized by much higher contents of organic carbon (2.7 to 43.4%) and are poor or very poorly drained. Their adsorptive capacities for passing cations depends mainly on the content of organic matter because clay minerals are poorly represented. Pokojska (1988) has found positive correlation (r = 0.72) between values of cation exchange capacities and the percentage of organic carbon content in those soils. Thus endoaquolls and medisaprists of the Turew landscape have high potential to adsorb cations (Pokojska 1988, Marcinek and Komisarek 1990). The area, from a Polish perspective, is warm, with an annual mean temperature of 8°C. Thermal conditions are favorable for vegetation growth. The growing season, with air temperatures above 5°C, lasts 225 days. On average, it begins March 21 and ends October 30. Mean corrected annual precipitation (1881–1985) amounts to 590 mm (uncorrected value to 527 mm). Although the amount of precipitation in the spring-summer period is more than twice that in winter, a water shortage often occurs in the summer. The annual evapotranspiration rate averages about 500 mm and runoff is 90 mm. Since a majority of the soils are characterized by high rates of infiltration, their water storage is not of great importance in dry summers. Water deficits are further intensified by drainage of a considerable part of the area. The most advantageous component of the landscape is its shelterbelts (rows or clumps of trees), which were planted in Turew due to the initiative of Dezydery Ch l apowski in the 1820s. In addition to shelterbelts, small afforestations are found in the landscape. Shelterbelts and afforestations cover 14% of the entire area and are composed of Pinus sylvestris (65.5% of total afforested area), Quercus petraea and Q. robur (14.5%), Robinia pseudoaccacia (5%), Betula pendula (4.3%) and others, totaling 24 tree species. But in shelterbelts oaks, false acacias, maples, lindens, larch, and poplars prevail. Oaks and larches have very deep root systems, while maples (especially sycamore maples) and lindens have moderately deep roots with broad root systems. The mix of the tree species creates a better screen to the seeping solutes in ground water than would a shelterbelt composed of one species (Prusinkiewicz et al. 1996). Cultivated fields cover 70% of the area. During the last 10 years, there has been a tendency for increased cereals (wheat, barley, rye, oats) in the crop rotation pattern, and it presently comprises 70% of arable land. Decreased row crops and pulse crops are also characteristic. Meadows and pastures located in depressions close to channels, ponds, and lakes and among cultivated fields cover 12% of the area. Hay forms the largest component of grasslands, but other important associations are made by sedge meadows in wetlands. The rest of the land is

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composed of lakes and mid-field ponds and channels, waterlogged areas, roads, and villages. The density of small reservoirs varies from 0.4 to 1.7/km2. Mineral fertilization varied from 220 to 315 kg NKP/ha but since 1991 about a 40 to 50% decrease or greater in mineral fertilization was observed on some small farms because of the economic crisis associated with the change of the political system. Yields are high for cereals (rye, wheat, barley and oats), ranging from 3.2 t·ha–1 to about 4 t·ha–1. The level of mechanization of field labor is high, amounting on the average to 1 tractor per 17 ha of cultivated fields. In studies on the impact on ground water chemistry from the mid-field afforestations and shelterbelts or strips of meadows (called biogeochemical barriers), the dominant direction of subsurface water pathways was estimated by measurement of ground water table elevation in wells located in fields and adjoining shelterbelts, small forests, or meadows. The samples for nitrogen compound concentration measurements were collected from wells, drainage pipes, ditches, small ponds, and main drainage canals of the landscape over different periods but never during a time span shorter than 1 year. Over the last 200 years, there were important habitat changes connected with land reclamation activities leading to drying of the area. The effects are observed not only in the drop in the ground water level but also in soil degradation caused by drainage. So, for example, fertile endoaquolls have been converted in many places into glossudalfs or hapludalfs with low carbon content. Thus, drying of the region is expressed in soil changes; although appearing slowly, the nature of the trend can be clearly recognized.

NITROGEN COMPOUNDS IN THE DRAINAGE SYSTEM OF THE TUREW LANDSCAPE The Turew landscape is drained by a canal about 4 m wide with an average longterm water depth of 0.6 m. The annual mean concentrations of N-NO3–1 varied irregularly from 0.5 mg·dm–3 to 3.4 mg·dm–3. Almost the same range of variation in N–NH4+ concentration was observed (Figure 5.1). At the beginning of the 1990s, there was a decline in the use of fertilizers due to the economic crisis, amounting to a drop in application of 40 to 50%. But despite decreased input of fertilizers, the level of inorganic ion concentrations of nitrogen did not change, showing irregular cycles with a peak in 1993 and 1994, followed by a drop and then increasing since 1997 (Figure 5.1). Mean concentrations of the mineral forms of nitrogen in the canal water during the period 1973–1991, when higher doses of fertilizers were applied, were 1.40 mg · dm–3 for N–NO3– and 1.70 mg·dm–3 for N–NH4+. In the period 1992–2000 when fertilizer use dramatically decreased, the mean concentration increased to 2.04 mg· dm–3 in the case of N–NO3– and to 1.81 mg·dm–3 for N–NH4+. Thus, the relationship between input of fertilizer and output of nitrogen ions from the watershed is not linear and is substantially modified by the buffering capacities of the total drainage area. The storage capacities of various elements in the landscape for nitrogen, as well as options for

19

0

0.5

1

1.5

2

2.5

3

73

Figure 5.1

Concentration [mg·dm-3]

3.5

74 19

75 19

76 19

77 19

78 19

79 19

80 19

81 19

82 19

83 19

84 19

85

19

86

8 19

7

19

88

89 990 991 992 993 994 995 996 997 998 999 000 1 1 19 1 1 1 1 1 1 1 1 2

Mean annual concentration in main drainage canal of the Turew landscape.

19

N – NH4+

N – NO3-

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Table 5.2

Mean Monthly Long-Term (1973–2000) Concentrations (mg·dm–3) of Inorganic Nitrogen Forms in Main Drainage Canal of the Turew Landscape in Consecutive Periods of the Year

Period

Dec.–Feb.

March–April

May–Sept.

Oct.–Nov.

N–NO3– N–NH4+

2.79 ± 1.01 1.98 ± 0.30

2.50 ± 0.71 1.92 ± 0.44

0.88 ± 0.15 1.68 ± 0.19

1.11 ± 0.48 2.10 ± 0.37

diverting nitrogen compounds into various routes of discharge (water runoff, volatilization), not only condition lag responses but also obscure the relationships between fertilizer input and their concentrations in water of the drainage system. The long-term (28 years) average concentration of both mineral forms of nitrogen was the same in the main canal of the Turew landscape — 1.69 mg·dm–3 in the case of N–NO3– and 1.74 mg·dm–3 for N–NH4+. Analysis of changes of N–NO3– and N–NH4+ ions over 28 years showed that the changes are independent (correlation coefficient r = –0.06 is not statistically significant), which is another indication of the complex transformation of nitrogen in the landscape. When the concentrations of nitrogen forms were analyzed with respect to the monthly changes during the year, distinct seasonal differences were found between the cold and growth seasons (Bartoszewicz 1994). During the winter (December–February), the monthly mean nitrate concentration was highest, reaching 2.79 mg·dm–3 (Table 5.2) while its value during the full plant growth season (May–September) was lowest. When the plant’s transpiration processes decreased in October and November (leaf shedding by deciduous trees, drying of grasses, and only small plants of winter crops present in cultivated fields), nitrate concentration increased so as to reach the highest values when biological activity is retarded in winter. Concentrations of N–NH4+ cations did not show such distinct changes in the course of seasons although some drop during the plant growth season can be easily observed (Table 5.2). In the course of the entire year, nitrates show much higher variance of concentrations than ammonium. It seems the reason for this difference is connected with the fact that biological activity is in “full swing” during the warm season, although pinpointing the specific process responsible (plant uptake, denitrification, assimilatory or dissimilatory nitrate reduction) requires additional studies. In the plant growing season (end of March until the end of October), average precipitation reaches 410 mm out of an annual total of 590 mm (Wos´ and Tamulewicz 1996). Despite high precipitation rates in summer, the concentrations of nitrates in water of the canal were low in this period, although N–NO3– anions are easily leached from soil. Thus, effects of mineral nitrogen leaching caused by rainfall are modified by influences exerted by plants on migrating nitrogen ions in the watershed. (This conclusion is confirmed by special studies carried out in small watersheds, the results of which are discussed later in this chapter.) The differences between nitrate concentrations in ground water under cultivated fields and their concentrations in water of the main drainage canal clearly show modification effects exerted by the landscape structure on dispersion of chemical

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compounds. Analyses of mineral nitrogen distribution in the unsaturated zone below the cultivated field showed that in the spring large amounts are leached into the ground water. In ground water of some fields, high concentrations of N–NO3–, reaching 60 mg·dm–3, can be found when fertilizers were applied during spring (Ryszkowski et al. 1997). But despite the fact that such situations occur in some fields, each spring the monthly concentrations of nitrates in the main canal draining the total area are very low, which again indicates strong modification effects of landscape structure on the control of diffuse pollution.

CONTROL OF MINERAL NITROGEN POLLUTION BY SHELTERBELTS AND MEADOWS When ground water carrying nitrates is within direct and indirect (capillary ascension) reach of the root system, nitrate concentrations are substantially decreased. Knowing that the NO3– anion is practically not exchanged by soil colloids, these differences result mainly from the action of a complex set of biological factors involving the plant’s uptake, denitrification processes, and release of gaseous products including NO, N2O, and N2. In addition, nitrates may undergo reduction to NH 4+, which could be volatilized. The regulation of those processes under field conditions is poorly understood (Correll 1997). The reduction of nitrates when ground water is seeping under shelterbelts, afforestations, or grasslands is pronounced, and under the Turew landscape conditions such reduction varied from 63 to 98% for shelterbelts and afforestations (Table 5.3). In the case of meadow strips, the reduction varied from 79 to 97%. Table 5.3

Mean Concentrations of N–NO3– (mg·dm–3) in Ground Water under Cultivated Fields, Shelterbelts, Small Forests, and Meadows in the Turew Agricultural Landscape

Period of Sampling

Cultivated Field (a)

Shelterbelt or Forest Patch (b)

Meadow (b)

Reduction (a-b):a (%)

1982–1986

22.2

1.0

—

95

1982–1986

37.6

1.1

—

97

1972–1973

12.6

0.3

—

98

1984–1986 1994 1995 1986–1989 1987–1989 1987–1991

33.1 52.4 13.1 48.3 15.9 13.1

8.1 2.7 4.9 — — —

— — — 6.5 0.7 2.8

75 94 63 87 95 79

1993 1993 1994 1994 1995

18.7 22.1 19.1 13.4 18.3

— — — — —

1.4 2.0 1.2 2.4 0.6

92 91 94 82 97

Reference Bartoszewicz and Ryszkowski 1996 Bartoszewicz and Ryszkowski 1996 Margowski and Bartoszewicz 1976 Ryszkowski et al. 1997 Ryszkowski et al. 1997 Ryszkowski et al. 1996 Bartoszewicz 1990 Bartoszewicz 1990 Szpakowska and · Zyczyn´ ska-Ba l oniak 1994 Ryszkowski et al. 1996 Ryszkowski et al. 1996 Ryszkowski et al. 1996 Ryszkowski et al. 1996 Ryszkowski et al. 1996

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Thus, both kinds of biogeochemical barriers (shelterbelts and meadow stretches) showed similar efficiency of nitrate reduction. Results are similar to the estimates gathered from various literature sources by Muscutt et al. (1993). One can argue that changes in concentrations do not fully show the effects of nitrate limitation exerted by the biogeochemical barriers. The control effects depend on both the changes in concentrations and the rate of N–NO3– flux through the barrier. Low concentration inflow can provide a large amount of chemicals if the rate of water flux is high. But the hydraulic conductivity of soils (up to 1.0 m·day–1) as well as hydraulic gradients of ground water tables that determine flux are small in the landscape studied, which should render good approximations of nitrate fluxes by changes in their concentrations. This situation was confirmed by studies of the hydrology of water seeping under biogeochemical barriers (Ryszkowski et al. 1997). Estimated N–NO3– ratios for output-input of annual flux estimates for birch mid-field forests amounted to 0.22, 0.25, and 0.28 in three consecutive years (Ryszkowski et al. 1997). The average for the 3 years was 0.25, which corresponds well with the estimate based on concentration changes, which was also 0.25. In the case of the pine mid-field forest, both estimates also match very well (Ryszkowski et al. 1997). Thus, in an area where the slope of the ground water table is not too steep, the differences in concentrations of chemical compounds between an input and output characterize well the flux control efficiency of the barrier. Studies (Ryszkowski and Ke˛ dziora 1993) indicate that, as the steepness of slope increases, the shelterbelt and meadow are less efficient in regulating ground water flow and chemicals transported. A great influence of plant cover structure on output of elements from watersheds was shown by Bartoszewicz (1994), and Bartoszewicz and Ryszkowski (1996). These studies were carried out in two small watersheds. The first was a uniform watershed (174 ha) covered 99% by cultivated fields and 1% by small afforestation. The second watershed (117 ha) was mosaic; cultivated fields made up 84% of the area, meadows 14%, and riparian afforestation 2%. During the 3-year period, the mean annual water output was 102.0 dm3 ·m–2 from the uniform watershed and 70.2 dm3 ·m–2 from the mosaic watershed. The mean annual precipitation for both watersheds was the same, amounting to 514 dm3 ·m–2, so the lower water runoff from the mosaic watershed was due to higher evapotranspiration rates characteristic of afforestations and grasslands (Ryszkowski and Ke˛ dziora 1987). This is clearly seen when water outputs are analyzed from both watersheds in summer (Table 5.4). The water runoff from both watersheds during the hydrological years 1988/1989–1990/1991 differed by 32 mm on average. However, the water runoff during the winter half-years was almost the same from either watershed, whereas during the growing season water outputs from the uniform watershed (per unit of area) were three times higher than those from the mosaic watershed (Bartoszewicz 1994). Thus, shelterbelts and meadows making up 16% of the mosaic watershed area very effectively controlled output of water from the catchment area into the drainage canal during the plant growing season (Table 5.4). From a uniform arable watershed, 20.4 kg of inorganic nitrogen had leached out from 1 ha annually, 20% of which was in the form of ammonium ions. Thus the

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Table 5.4

Season Winter Nov.–April Summer May–Oct. Whole year

121

Annual Mean Water Output (mm) and Nutrient Loss (g·m–2 ·year–1) from Two Small Watersheds, Nov. 1988–Oct. 1991

Precipitation (mm)

Uniform Watershed Water Output (mm) N–NO3– N–NH4+

Mosaic Watershed Water Output (mm) N–NO3– N–NH4+

220.7

60.8

12.3

3.0

56.8

0.90

0.95

292.9

41.2

4.0

1.1

13.4

0.05

0.25

513.6

102.0

16.3

4.1

70.2

0.95

1.20

Source: Bartoszewicz 1994.

preponderance of nitrates over ammonium is clearly evidenced in water output from the uniform agricultural drainage area. When the migration of mineral components from a mosaic watershed was analyzed, a low leaching rate of nitrogen constituents and a different ratio of nitrates to ammonia ions were observed. The annual leaching rates of mineral N from 1 ha of this watershed amounted to about 2 kg (ten times less than in the uniform watershed), and both ionic forms of N were represented by almost identical shares. Even more striking were the differences between the uniform arable watershed and the mosaic one with respect to seasonal variations in the migration of nitrogen. The majority of both nitrogen ion forms (86%) had leached from the mosaic watershed in the winter half-year, while during the plant growth period the leaching of either nitrogen form (particularly of nitrates) was negligible (Table 5.4). The study of nitrogen leaching from the small watersheds with different plant cover structures supports the conclusion that shelterbelts, strips of meadows, and other biogeochemical barriers located both in upland and riparian parts of the Turew landscape effectively control the discharge of nitrogen from the drainage area. This conclusion explains the low concentrations of its mineral forms in the main canal (Figure 5.1). The smaller variability of ammonium cations in contrast to nitrates during the course of the year observed in the main Turew canal (Table 5.2) as well as the dissimilarity of these compound shares in discharge from the uniform and mosaic small watersheds (Table 5.4) indicate differentiated impacts of plant cover structures on dissemination of these inorganic forms of nitrogen in the landscape. Contrary to nitrates, the concentrations of ammonium cations usually do not decrease when ground water is passing under shelterbelts or meadows. Comparing concentrations of N–NH4+ in ground water under cultivated fields and shelterbelts or grass strips one observes increased rather than decreased amounts of N–NH4+ (Table 5.5). Because some ammonium ions incoming with ground water from fields are absorbed by plants, the lack of a decrease in their concentrations under shelterbelts or meadows certainly indicates that N–NH4+ cations are released from the internal cycle of nitrogen in the biogeochemical barrier. The influence of precipitation on leaching of nitrogen forms from litter and soil into ground water is a well-known phenomenon. Both the precipitation intensity and

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122

Table 5.5

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Mean Concentrations of N–NH4+ (mg·dm–3) in Ground Water under Cultivated Fields, Shelterbelts, Small Forests, and Meadows in the Turew Agricultural Landscape

Period of Sampling

Cultivated Field (a)

Shelterbelt or Forest Patch (b)

Meadow (b)

Reduction (a–b):a (%)

1982–1986

2.5

2.0

—

25

1982–1986

2.1

4.5

—

114a

1972–1973

1.4

2.7

—

–92

1984–1986 1994 1986–1989 1987–1989 1987–1991

1.7 1.3 1.8 1.8 1.8

1.7 1.1 2.2 2.1 —

—

2.2

0 15 –22 –16 –22

1993 1993 1994 1994 1995

2.4 2.5 2.6 3.9 2.5

— — — — —

2.4 2.4 3.0 7.1 4.0

0 4 –15 –82 –60

a

Reference Bartoszewicz and Ryszkowski 1996 Bartoszewicz and Ryszkowski 1996 Margowski and Bartoszewicz 1976 Ryszkowski et al. 1997 Ryszkowski et al. 1997 Bartoszewicz 1990 Bartoszewicz 1990 Szpakowska and · Zyczyn´ ska-Ba l oniak 1994 Ryszkowski et al. 1996a Ryszkowski et al. 1996a Ryszkowski et al. 1996a Ryszkowski et al. 1996a Ryszkowski et al. 1996a

Minus values mean increase of concentration under the biogeochemical barrier.

annual distribution are of considerable significance. In studies of mosaic and uniform small watersheds in the hydrological years of 1989/90 and 1990/91, during which the sums of precipitation were at the level of 550 mm·year –1, the losses of nitrogen forms were much higher (in some instances twice as high) than in the hydrological year 1988/1989, during which the annual precipitation was 110 mm lower. In the case of nitrates, the pattern of annual precipitation distribution rates plays a significant role. When intensive rains occurred during the late autumn and winter of 1990/91 — i.e., at a time when appreciable amounts of nitrates were being released from the decomposing post-harvest plant remnants (Ryszkowski 1992) — the leaching of nitrates was 6 kg higher than in 1989/90 when precipitation was lower by 40 mm.

PROCESSING OF MINERAL NITROGEN IN THE BIOGEOCHEMICAL BARRIERS In order to study the distribution of mineral forms of nitrogen in the unsaturated zone of the soil profile, the method of moisture saturation extracts was used (Jackson 1964). According to this method, soil samples are treated with distilled water to saturation and then centrifuged to obtain extracts from which the concentration of chemical compounds is determined. Then, using conversion equations, one can estimate the content of chemicals in the unsaturated layer of soil. In the pine afforestation and adjoining cultivated field located on hapludalf soils in the upland

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Table 5.6 Distribution of N–NO3– and N–NH4+ (g·m–2) in the Unsaturated Layers of Soil in the Cultivated Field and Adjoining Pine Afforestation

Sampling Term

Mineral Form of N

Cultivated Field Soil Layer Depth (cm) 0–80 81–150 0–150

Pine Afforestation Soil Layer Depth (cm) 0–80 81–150 0–150

April 1986

N–NO3– (a) N–NH4+ (b) Sum a:b

13.9 2.3 16.2 6.0

7.9 4.9 12.8 1.6

21.8 7.2 29.0 3.0

5.2 6.7 11.9 0.8

1.1 3.3 4.4 0.3

6.3 10.0 16.3 0.6

September 1986

N–NO3– (a) N–NH4+ (b) Sum a:b

3.7 1.6 5.3 2.3

1.2 0.9 2.1 1.3

4.9 2.5 7.4 1.9

0.3 2.1 2.4 0.1

0.2 0.5 0.7 0.4

0.5 2.6 3.1 0.2

April 1987

N–NO3– (a) N–NH4+ (b) Sum a:b

9.7 1.7 11.4 5.7

8.6 0.3 8.9 28.6

18.3 2.0 20.3 9.1

2.8 3.9 6.7 0.7

1.0 0.8 1.8 1.2

3.8 4.7 8.5 0.8

May 1998

N–NO3– (a) N–NH4+ (b) Sum a:b

0.4 2.2 2.6 0.2

4.5 1.1 5.6 4.0

4.9 3.3 8.2 1.5

0.7 2.4 3.1 0.3

2.9 1.7 4.6 1.7

3.6 4.1 7.7 0.8

September 1998

N–NO3– (a) N–NH4+ (b) Sum a:b

5.5 1.9 7.4 2.9

1.9 1.2 3.1 1.6

7.4 3.1 10.5 2.4

1.3 3.3 4.6 0.4

0.7 1.6 2.3 0.4

2.0 4.9 6.9 0.4

Source: Modified after Bartoszewicz 2001a, Ryszkowski et al. 1997.

part of the watershed, soil samples were taken at different depths of soil profile during the 1986–1987 period (Ryszkowski et al. 1997). Almost 10 years later, again in the same place, soil samples were collected for moisture saturation extracts (Bartoszewicz 2001a). Comparing the distribution of inorganic nitrogen in soil profiles at various seasons in afforestation and adjoining fields, one can find higher concentrations of ammonium cations in the soil profile under afforestation than under the cultivated field. In the case of nitrates, the opposite situation was found (Table 5.6) as a result of more intensive nitrification processes due to the better soil aeration caused by tillage. The input of fertilizers resulted in higher concentrations of nitrogen mineral forms in the soil of the cultivated field. Applied nitrogen fertilizers consisted mainly of ammonium nitrate (NH4NO3), so the same amounts of both nitrogen forms were introduced into soil. Domination of nitrates indicated, therefore, intensive nitrification processes in the cultivated field soil due to aeration caused by tillage. Comparisons of nitrogen ions concentrations at consecutive terms of sampling in April and September 1986 and April 1987, as well as those concentrations in May and September 1998, were conducted in the same field and afforestation located on hapludalf soil (Table 5.6), and they indicate clear fluctuations of these ions in the soil profile. At least some of these changes are caused by leaching of ions into the ground water. One has to remember that uptake of ions by plants also influences

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Table 5.7 Distribution of N–NO3– and N–NH4+ (g·m–2) in the Unsaturated Layers of Soil under Cultivated Field and Newly Planted Shelterbelt Sampling Term

Mineral Form of N

Cultivated Field Soil Layer Depth (cm) 0–80 81–150 0–150

New Shelterbelt Soil Layer Depth (cm) 0–80 81–150 0–150

October 1999

N–NO3– (a) N–NH4+ (b) Sum a:b

4.8 1.7 6.5 2.8

17.8 0.4 18.2 44.5

22.6 2.1 24.7 10.7

0.4 1.0 1.4 0.4

0.6 0.6 1.2 1.0

1.0 1.6 2.6 0.6

May 2000

N–NO3– (a) N–NH4+ (b) Sum a:b

4.0 1.2 5.2 3.3

11.5 0.4 11.9 28.7

15.5 1.6 17.1 9.6

1.1 1.7 2.8 0.6

0.1 0.3 0.4 0.3

1.2 2.0 3.2 0.6

Source: Modified after Bartoszewicz 2001a.

the distribution of nitrogen ions in the soil profile; in the majority of performed determinations, lower concentrations of nitrogen ions were observed in the soil strata below 80 cm depth (Table 5.6) as a result of ion uptake by root systems. Lack of direct measurements of water infiltration fluxes through soil profile obscures the precise estimates of nitrates and ammonium inputs into ground water from the unsaturated zone of soil with percolating water after precipitation events. Nevertheless, comparisons of nitrates and ammonium concentrations in ground water under fields and afforestations or meadows (Tables 5.3 and 5.5) clearly demonstrate that nitrates are reduced by those biogeochemical barriers while ammonium ions are not. In order to evaluate the influence of shelterbelts on mineral nitrogen in the soil the special studies were done on the distribution of inorganic nitrogen in the soil profile 6 years after trees were planted on a cultivated field with hapludalf soils. In soil withdrawn from cultivation for 6 years, very low concentrations of mineral nitrogen were detected in comparison with an adjoining cultivated field (Table 5.7). When inputs of fertilizers into soil under a growing shelterbelt were ceased, the amount of mineral nitrogen dramatically decreased almost 10 times in comparison with a field in October 1999 and 5 times in May 2000 when mineral nitrogen was regenerated due to greater decomposition rates brought by the higher temperatures of spring. The levels of mineral nitrogen in the soil under newly planted shelterbelts were lower than in soil under a 60-year-old afforestation planted also on the same hapludalf soils (compare Tables 5.6 and 5.7). This phenomenon is caused by the low level of litter and soil organic matter accumulation in a new shelterbelt due to short time lapse after tree planting. Decomposed organic matter is an important source of mineral nitrogen stocks in soil (this process is discussed with results of urease activity studies later in this chapter). In the new shelterbelt, ammonium ions predominate over nitrates, which resembles the situation in the old afforestations and shelterbelts, indicating that the preponderance of N–NH4+ is very quickly established when soil is withdrawn from cultivation.

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The other study of Bartoszewicz (2000) on the newly planted shelterbelt growing on endoaquolls showed that after 1 year of seedling growth, the ratio of N–NO3– to N–NH4+ was already 0.8 (1.5 g·m–2 and 1.7 g·m–2, respectively) while in the same adjoining soil but under cultivation this ratio was 2.7 (3.5 g·m–2 and 1.3 g·m–2, respectively) in soil profiles to 150 cm of depth. This last result indicates that withdrawal of tillage activities alone has important bearing on decreased nitrification processes due to poorer soil aeration, although the levels of mineral nitrogen in organic-rich soil (endoaquolls) showed differences not as great between field and new shelterbelt (total mineral nitrogen in cultivated soil amounted to 4.8 g·m–2 and in 1 year the old shelterbelt was equal to 3.2 g·m–2). Some ammonium ions are absorbed by roots as well as retained by the baseexchange complex, especially in the deeper strata of soil in the Turew landscape (see Table 5.1 for values of cation exchange capacities [CEC] and percent of saturation of sorption complex [BS]). The observed lack of decrease in N–NH4+ ions concentrations when ground water is passing through root systems of the biogeochemical barriers (Table 5.5) should be related, therefore, to inputs of ammonium ions from decomposing organic matter. Several biological processes could lead to production of N–NH3. The first process is assimilatory nitrate reduction in which N–NH3 is used for production of biomass, (proteins) which after mineralization could release ammonium ions. Assimilatory nitrate reduction takes place under oxygenic conditions. The second process is actually two processes: dissimilatory reduction of nitrates, which in denitrification releases gaseous forms of nitrogen, and in dissimilatory reduction of nitrate to ammonium releases N–NH4+ ions under anaerobic conditions (Tiedje et al. 1981). In addition, very small amounts of N–NH4+ can be exuded from tree roots as shown experimentally by Smith (1976) in the case of birch, beech, and maple trees. In all plants, ammonia (NH3) plays a key role in nitrogen assimilation because all nitrogen organic compounds are derived from ammonia assimilation regardless of the nutritional source of nitrogen to plants. Plant proteins and nucleic acids are built from low molecular organic compounds deriving nitrogen from the NH3 form. Thus, nitrates absorbed by plants are converted by assimilatory nitrate reduction to ammonia, and in this form nitrogen is incorporated into the biomass. When plant tissues undergo decomposition, ammonia ions are released. This last process is controlled at the final stage by the enzyme urease, which is responsible for the conversion of urea nitrogen to ammonia nitrogen (Bremner and Mulvaney 1978). Urease activity analysis therefore monitors the release of N–NH3 from decomposing organic compounds in the soil, which in soil solution appears as N–NH4+. In studies reported here, urease activity was measured by the Hoffman and Teicher method described and calibrated by Szajdak and Matuszewska (2000). The urease activity was measured in the upper layer of soil (0–20 cm of depth) in the 7-year-old shelterbelt as well as the 140-year-old shelterbelt and adjoining fields. Both shelterbelts were planted on hapludalf soils. The urease activity was studied by L. Szajdak in the 7-year-old shelterbelt 1 year later than studies on distribution of mineral nitrogen forms in the soil profile presented in Table 5.7 were conducted.

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Table 5.8 Urease Activity (UA; µg urea hydrolyzed·g–1soil·h–1), Organic Nitrogen (ON; mg·kg–1) in Soils of Various Ecosystems in the Turew Landscape Shelterbelts 7-Year-Old 140-Year-Old UA ON UA ON

Fields Adjoining to Shelterbelts 7-Year-Old 140-Year-Old UA ON UA ON

March 12 April 7 May 8 June 5 July 9 August 20 September 14 October 12 November 14

4.35 4.81 4.56 4.25 6.20 9.17 7.76 5.07 4.35

590.5 591.8 609.1 527.3 602.7 571.4 538.4 657.3 549.1

16.88 14.50 18.96 5.32 4.88 3.58 7.94 4.05 2.15

1634.3 1677.3 1416.5 2541.4 5644.9 3400.7 2138.0 3133.0 2320.7

6.45 5.98 7.25 5.27 5.30 8.40 5.30 3.40 3.07

354.8 350.6 355.1 497.1 421.2 472.4 506.4 488.9 501.2

4.53 4.38 3.94 2.50 2.67 6.41 7.92 2.63 1.93

587.5 567.8 533.3 789.1 576.7 566.1 460.3 521.1 506.9

Mean

5.61

581.9

8.69

2656.3

5.60

438.6

4.10

567.6

Date

According to the review by Bremner and Mulvaney (1978), urease activity is positively related to organic matter content due to microbial and plant metabolism, and its activity is high in soils under dense vegetation. Clay content to some extent protects urease against decomposition. Mineral fertilizers (e.g., ammonium nitrate) and soil oxygenation have no effects; slight effects are exerted by levels of soil moisture, but a rapid sequence of drying and rewetting of soil decreases its activity. Fluctuations of urease activity are characteristic both for shelterbelts and cultivated fields (Table 5.8). Despite detected variability, the average values of urease activities in soil of the 7-year-old shelterbelt and adjoining cultivated field as well as a field adjacent to the 140-year-old shelterbelt were similar. The rate of urea [CO(NH2)2] hydrolysis into CO2 and NH3 brought by catalytic activity of urease depends on its concentration. Assuming that organic nitrogen contents in soil (estimated as the difference between nitrogen estimated by the Kjeldahl method [without reduction of nitrates] and N–NH4+), may be used as an index of urea concentrations, the similarity of urease activity in these three ecosystems can be explained by the same levels of substrates available for decomposition (Table 5.8). Soil under the 7-year-old growing shelterbelt did not store enough organic nitrogen, part of which could undego decomposition and provide significantly higher levels of urea concentration. But during the 140 years since the trees were planted on hapludalf soils, the organic matter accumulated in soil and the average contents of organic nitrogen are almost fivefold higher than in the adjacent field. In response to this increase the amounts of hydrolyzed urea almost doubled (Table 5.8). Thus, in shelterbelts not only is conversion of nitrates into ammonium ions by assimilatory nitrate reduction observed, but release of N–NH3 during decomposition of biomass is also observed. Because of the organic nitrogen accumulation during the growth of the shelterbelt, the amounts of urea available for decomposition also increase, which results in higher production of N–NH3 due to activity of urease although this relationship is not linear. In the 7-year-old shelterbelt, the ratio of organic nitrogen to urease activity is 581.9: 5.61 = 103, and in the 140-year-old shelterbelt this ratio is 2656.3:

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8.69 = 305. Thus, in the older shelterbelt more organic nitrogen is not decomposed into urea but stored in resistant-to-decomposition form. Nevertheless, when soil sorption capacities as well as nutritional demands of plants are met, then higher rates of leaching ammonium ion can be expected in older shelterbelts rather than in young ones, where low amounts of organic nitrogen are accumulated. Interplay of these processes explains the results presented in the Table 5.5, showing the efficacy of biogeochemical barriers for control of ammonium ions seeping with ground water through the root systems of plants. In 9 of 13 analyzed cases, no decreases were detected when output-to-input N–NH4+ concentrations were analyzed. Efficient uptake of nitrates by plants in biogeochemical barriers and their processing by biota into N–NH4+ also explain lower variation of ammonium ions than nitrates in the main drainage canal during the course of the year (Table 5.2). How much N–NH4+ is leached into ground water depends on the complicated interplay of several processes. Released N–NH4+ ions from decomposing organic matter could again be taken up by organisms for production of their biomass, converted to nitrates in nitrification processes, withdrawn from soil solution by sorption complex, incorporated into stored inert organic nitrogen, or leached into ground water. Moreover, ammonia (NH3) could be volatilized into air. Because intense NH3 volatilization appears from soil solutions when its reaction is above 7 pH, one can assume that this is not a significant form of ammonia loss from the Turew landscape soils, but drying of soils and high air temperature could have some effects on this process (Freney et al. 1981, Harper et al. 1996). The losses of NH3 by volatilization may be reduced to some extent by the repeated absorption of released ammonia by plants when this gas is still within a vegetation stand (Harper et al. 1995). Due to those various recycling processes, the ammonia emissions from forests are small (Longford and Fehsenfeld 1992). All those processes are influenced by physical and chemical factors, but the central role is played by the biological processes of assimilation, decomposition, nitrification, and denitrification. In the young and old shelterbelts and adjoining fields studied, CO2 and N2O evolution were measured. Carbon dioxide and nitrous oxide concentrations in gas samples were determined with Varian GC 3800, equipped with an electron capture at an operating temperature of 340°C and with a thermal conductivity detector operating at a temperature of 200°C. A Porapak 1.8-m Q 80/100 column (Alltech Associates, Inc., Deerfield, IL) at 50°C was used to separate N2O, and at 74°C to separate CO2 (Cabrera et al. 1993). Evolution of CO2 from soil can be used as an index of general biological activity of the cultivated fields and shelterbelts studied. The highest mean of CO2 evolution was found from the soil of the 140-year-old shelterbelt while the two fields and the 7-year-old shelterbelt were characterized by similar (not statistically significant) rates of CO2 evolution (Table 5.9). More than fourfold higher organic nitrogen contents found in soil of the older shelterbelt compared to an adjacent field was associated with only 56% higher CO2 evolution, which again indicates that the relationship between nitrogen organic matter and soil metabolic activity is not directly proportional to the increase of the potential substrate for decomposition.

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Table 5.9 CO2 Evolution (g·m–2 ·h–1) from Soil in Shelterbelts of Various Ages and Adjoining Cultivated Field Date

Shelterbelts 7-Year-Old 140-Year-Old

March 12 April 7 May 8 June 5 July 9 August 20 September 14 October 12 November 14

82 83 84 86 88 87 83 82 79

119 120 141 146 167 159 155 123 119

Mean

83.8

138.8

Fields Adjoining Shelterbelts 7-Year-Old 140-Year-Old 82 82 87 91 115 107 87 83 85 91

79 78 81 100 129 99 83 80 68 88.6

With increasing age of shelterbelt, more and more nitrogen is stored in the resistant-to-decomposition organic compounds. The accumulation of soil organic matter under shelterbelts is the main mechanism of long-term withdrawal of various elements from the dynamic cycle of transformations in an ecosystem. Absorbed by plants or microbes, nutrients become built into plant biomass; then after the decay of biomass some of them are stored in humus. Estimates of the withdrawal rates of nitrogen into humus provided the figure of 1.7 g·m–2 ·year –1 in the 140-year-old shelterbelt and 1.4 g·m–2 ·year–1 for pine afforestation planted on hapludalf soils (Ryszkowski et al. 1997). Some nitrogen is also withdrawn from circulation for a considerable time in woody parts of trees. In the case of the pine afforestation this form of nitrogen storage attains a value of 0.0022 g N·m–2 ·year–1 (Ryszkowski et al. 1997) and is much lower than incorporation of nitrogen into humus. The highest level of organic nitrogen in the soil of the old shelterbelt was also correlated with very clear seasonal changes in the CO2 evolution, reaching the highest values in the warmest months (July and August) of the year. The most intensive evolution of the nitrous oxide from soil was also observed in the summer (Table 5.10). Table 5.10 N2O Evolution (N g·m–2 ·h–1) from Soil in Shelterbelts of Various Ages and Adjoining Cultivated Fields Date March 12 April 7 May 8 June 5 July 9 August 20 September 14 October 12 November 14 Mean

Shelterbelts 7-Year-Old 140-Year-Old

Fields Adjoining Shelterbelts 7-Year-Old 140-Year-Old

80 80 80 120 120 110 100 90 100

120 110 130 130 180 170 150 150 140

200 240 220 370 320 250 190 200 170

250 230 250 270 280 270 250 240 240

97

142

240

253

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From the soil of cultivated fields, where nitrates prevail over ammonium ions (Tables 5.3, 5.6, and 5.7), much higher rates of N2O evolution were observed than from the soil of shelterbelts where ammonium dominates or makes a substantial contribution to the pool of mineral nitrogen. This result confirms estimates of Robertson et al. (2000) indicating that N2O fluxes are much higher from soil under annual crops than from poplar cultivation. With higher amounts of nitrates in soil, rates of N2O evolution are also greater, though this relation is not linear and strongly depends on distribution of anaerobic sites in the soil. In the newly planted shelterbelt, where shortage of nitrates is apparent (1.0 to 1.2 g·m2 in 150-cm-deep soil stratum, Table 5.7) the evolution of N2O was the lowest. Converting the annual rates of nitrogen storage in humus and wood production into hourly intervals for the sake of comparison with N2O evolution, 160 µg N·m–2 ·h–1 is found for pine afforestation and 190 µg N·m–2 ·h–1 for the 140-yearold shelterbelt. These rates are very similar to those for N2O evolution in the old shelterbelt (Table 5.10). The rate of the nitrogen storage in wood is lower and after conversion is 22 µg N·m–2 ·h–1. One can infer that nitrogen storage in shelterbelt humus is greater than its storage in wood, and that both long-term storage mechanisms operate at the same level such as the release of nitrogen in N2O evolution. The intensive conversion of nitrate inputs to ammonium ions through assimilatory reduction and then decomposition of organic nitrogen, releasing ammonium, as well as the low intensity of nitrification processes are the reasons for lower rates of N2O release into atmosphere in shelterbelts than in cultivated fields. Nitrification was not studied in the Turew landscape, but many researchers found low rates of nitrification in the terrestrial ecosystems with an unfertilized permanent vegetation (Verstraete 1981). The conversion of N–NO3– into N–NH4+ constitutes, as one can hypothesize, a nitrogen-saving mechanism in shelterbelts or meadows, preventing nitrogen loss by nitrate leaching and N2O evolution. Those nitrogen-saving mechanisms are evidenced by lower nitrate concentrations in ground water of the biogeochemical barriers than under fields (Table 5.3) and lower rates of N2O evolution in the shelterbelts than in cultivated fields (Table 5.10) and generally low concentrations of ammonium ions both in ground water under cultivated fields and biogeochemical barriers (Table 5.5). The lower rates of N2O evolution were directly measured. Considering operation of nitrogen-saving mechanisms in shelterbelts and meadows, the question still remains of how intensive is the release of N2 in denitrification processes. In addition, field measurements of NH3 volatilization should show if, as the literature suggests, very low rates of NH3 loss in the Turew upland soils represent the real situation.

LANDSCAPE MANAGEMENT GUIDELINES FOR EFFICIENT CONTROL OF NITROGEN POLLUTION The above analysis indicates that transformations of mineral nitrogen to organic forms and vice versa play a crucial role in control of nitrogen fluxes in the landscape.

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Nitrate input with precipitation in the Turew landscape, which makes up quite a substantial source,* as well as nitrate water runoff from cultivated fields are effectively controlled by the network of biogeochemical barriers that results in low mineral nitrogen concentrations in the main drainage canal. The mean annual mineral nitrogen (N–NO3– plus N–NH4+) varied over a 28-year period within 1.5 mg·dm–3 to 6 mg·dm–3 (Figure 5.1). The landscape mechanisms of control kept nitrogen concentrations at this rather stable level despite dramatic decrease in fertilizer use, changes in crop rotation patterns, and various weather conditions. From the landscape management point of view, an interesting question is what should be the size of the area that should be covered by biogeochemical barriers to efficiently control diffuse pollution. The answer will be provided in three steps that reflect varying degrees of complexity. The first step concerns the evaluation of the effective width of the biogeochemical barrier. The second step is the functional relationship between buffer zone area and output of nitrates from the watersheds. The third step deals with the management of nitrogen storing capacities in shelterbelts. Using the model of solar energy partitioning for various components of the heat balance of a large area incorporating meteorological characteristics and parameterization of plant cover structure developed by Olejnik (1988), Ke˛ dziora et al. (1989), Olejnik and Ke˛ dziora (1991), Ryszkowski and Ke˛ dziora (1993), Ryszkowski et al. (1997) estimated evapotranspiration rates of birch and pine afforestations under field conditions during the plant growth seasons for 10-day intervals. Estimates of evapotranspiration were then corrected for values of evaporation in order to obtain only plant stand transpiration estimates. Additionally, inputs of ground water from field into birch or pine afforestations through the 1 m × 2 m phreatic plane were estimated by special hydrological studies (Ryszkowski et al. 1997). Estimates of transpiration rates per square meter and the amount of ground water discharged from field into forest by under-surface flux were used to calculate the length of land band, under trees of 1-m width, necessary to transpire the incoming water. Thus, the subsurface water input was divided by the amount of water transpired by plants from 1 square meter. The length of that band was assumed to constitute an approximation of shelterbelt width necessary to perform effective removal of incoming mineral forms of nitrogen. Those calculations rely on the assumption that uptake of nitrates and ammonium ions by plants is mainly determined by water mass uptake for transpiration and that effects of the absorption by diffusion processes are small. In these calculations describing a selective performance of plants for uptake, various mineral forms of nitrogen found in some studies (see, for example, Kirkby 1981, Prusinkiewicz et al. 1996) were not taken into account. 1996 among others). Regarding selective uptake of nitrogen mineral forms, Prusinkiewicz et al. (1996) show that in periods of high water consumption the differences between the uptake of NH4+ ions and NO3– ions diminish, while at low water consumption increased selection for nitrates is observed. One has to keep in mind that because of these * The annual mean concentrations of N–NO3– in rain varies in the Turew region from 1.7 mg·dm–3 to 2.2 mg·dm–3 and ammonium from 2.6 mg·dm–3 to 5.1 mg·dm–3.

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inaccuracies, this proposed method of nutrient uptake estimation of an intact forest stand provides only approximations. Width of effective biogeochemical barriers during the plant growing season was estimated to vary from 5 m to 25 m in birch afforestation. The season-long mean was equal to 10.4 m. In pine afforestation, the estimates of effective width of biogeochemical barrier varied from 2.4 m to about 10 m, with an average value of 5.8 m. The differences between means were statistically significant, but the reason for it was probably not differentiated plant uptake by coniferous and deciduous trees but rather the poor stand of trees in the birch afforestation (Ryszkowski et al. 1997). One can assume, therefore, that the effective width of shelterbelt under Turew landscape conditions is about 6 to 8 m. This estimate was obtained for small slopes of ground water table and thus for slow ground water fluxes. For greater fluxes (e.g., higher water table slopes), the water will be passing faster and effectiveness of a given width of shelterbelt will be smaller. Ryszkowski and Ke˛ dziora (1993) show that the uptake of ground water by a 10-m wide shelterbelt or meadow can be so great on a warm and sunny day, having net radiation of 100 W·m–2, that flux of ground water is reduced almost completely if the ground water table steepness is 0.01. Under the same meteorological conditions but with the ground water table steepness of 0.04, the water flux is reduced by only 33%. These studies also show that shelterbelts have greater impact on ground water fluxes than meadow strips of the same width (Ryszkowski and Ke˛ dziora 1993) which explains the findings of Haycock and Pinay (1993) that grass riparian zones were less effective in control of nitrate pollution than were poplar riparian strips. The estimates of buffer barrier width for control of nitrates found by other scientists range from 5 m to 30 m. Individual estimates were as follows: 5 m (Cooper 1990), 8 m (Haycock and Burt 1991), 16 m (Jacobs and Gilliam 1985), 19 m (Peterjohn and Correll 1984), and 30 m (Pinay and Decamps 1988). Despite different interpretations of these estimates presented by various scientists, results are quite similar. In view of results obtained in the Turew landscape, efficient removal of nitrates from ground water is related to their uptake by plants with transpired water but not mainly with denitrification processes as claimed by many authors studying riparian vegetation strips. To disclose the relationship between an area of watershed covered by biogeochemical barriers and the output of nitrates, the studies were done on N–NO3– concentration in the water discharged in ditches from six small watersheds situated in the studied landscape (Ryszkowski 2000). The studies were carried out from November 1995 until December 1996. The area of the watershed varied from 75 to 216 ha. Cultivated fields have hapludalf and glossudalf soils. The watersheds varied with respect to contribution of arable fields which ranged from 99 to 52% of total area. Meadows, shelterbelts, and small forests represented the perennial vegetation. Each watershed was drained by ditch from which water samples were taken every 2 weeks. It was found that the exponential relationship characterizes well the relation between the share of biogeochemical barrier area in total watershed and N–NO3– concentrations in draining ditches (Figure 5.2). During the entire plant growing season two very intense rainfalls occurred. During the first 10 days of May, 1996, very heavy

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Plant growth season excluding heavy rains 16

y = 8.6287e-0.05

N-NO3 [mg ·l-1]

14 12

R2 = 0.8114

10 8 6 4 2 0

0

10

20

30

40

50

Share of nonarable area [%]

Winter season 16

y = 10.626e-0.035

14

R2 = 0.9616

N-NO3 [mg· l-1]

12 10 8 6 4 2 0 0

5

10

15

20

25

30

35

40

45

50

Share of nonarable area [%]

Heavy rains during plant growth season

N-NO3 [mg· l-1]

16 14

y = 14.251e-0.02

12

R2 = 0.9101

10 8 6 4 2 0 0

5

10

15

20

25

30

35

40

45

50

Share of nonarable area [%] Figure 5.2

Influence of plant cover structure (x) on N–NO3– concentration (y) in water output from small drainage basins.

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rains amounted to 106.4 mm, and at the beginning of July there was a second heavy rainfall of 111.1 mm. Measurements of N–NO3– concentrations in ditch water runoff associated with these precipitation events were analyzed separately because of the appearance of intense surface flows. The exponent of the equation characterizing the relationship between the share of buffer zones in the total area of watershed and N–NO3– concentration was higher for the plant growing season than for winter (Figure 5.2). This result can again be interpreted as caused by transpiration activity of plants — transpiring plants take up nutrients from soil solutions. Thus, greater area coverage by perennial plants with high transpiration rates shows larger uptake of nutrients and greater purification effect exerted by plants on diffuse pollution by nitrates. The lowest exponent value was found when heavy rains occurred. It seems that concentrated surface runoff caused by heavy rains masks to some extent the effects of biogeochemical barriers. Nevertheless, one can find a correlation between N–NO3– concentrations and buffer zone areas even in the case of heavy rainfall (Figure 5.2). The finding that the relationship between the share of biogeochemical barrier areas and nitrate concentration shows exponential character has an important bearing on landscape management practice. The small area under planted shelterbelts or grass strips shows unproportionally high control effects compared with those gained when it is extended to a larger size. That implication is true, of course, when biogeochemical barriers are strategically distributed with regard to directions of water runoff from the watershed. Permanent vegetation located in one patch will not exert such a control effect as would a network of shelterbelts and grass strips of the same area size. The network of biogeochemical barriers enables, therefore, optimization of the area withdrawn from agricultural production with arable land with respect to the economic issues of farming. In other words, the knowledge of the exponential effect exerted by the area under shelterbelts on water cleansing can help make economic decisions about the area of land that should be withdrawn from agricultural production for introduction of permanent vegetation strips. Uptake of both nitrogen mineral forms by plants and the subsequent formation of NH4+ ions during biomass decomposition play a crucial role in regulation of nitrogen cycling in an ecosystem. One can therefore hypothesize that when NH4+ released during decomposition of organic nitrogen overcomes its storage in long-term withdrawal processes (incorporation into humus or in woody tissues) as well as its maintenance in dynamic recycling between various biota (plants, microbes, animals), the biogeochemical barrier turns from N sink to its source in the landscape. It can be presumed, therefore, that when accumulated plant litter is rapidly decomposed because of favorable conditions, substantial amounts of nitrogen are leached through the soil profile, and its concentration will increase in ground water under the biogeochemical barrier. This situation was documented in studies on nitrogen leaching from the old, mixed species afforestation (a manor park) located in the Turew agricultural landscape. The park is overgrown by a stand of very old trees that has existed as a park for more than 200 years, and there are some pedological indications that its territory was never tilled. The upper part of the park

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Table 5.11 Nitrogen Loss from Litter in Park Afforestation Located on Hapludalf Soils

Period April 23–June 18, 1996 July 15–September, 1996 November 28, 1996– March 27, 1997 May 27–July 22, 1997 September 15– November 10, 1997

Decomposition Rate k of Litter/day (Wt = Woe–kt )

Average Mass of Litter (g·m–2)

Loss of Nitrogen (mg·dm–2 ·24h)

0.0032 0.0042 0.0034

483.1 312.2 641.0

43.6 27.0 31.2

0.0046 0.0038

464.0 285.8

94.1 53.9

Source: Z. Bernacki (unpublished data).

is located on hapludalf soils. The park is kept as a nature reserve and no management practices are carried out. Along the direction of ground water flux from the cultivated field, through the park and then to the pond, piezometers were installed for sampling ground water chemistry. It was dry in 1996, and the decomposition rate of litter was low, especially low in autumn and winter, which resulted in accumulation of plant litter. After the fall of leaves, the average mass of litter reached 641 g · m–2 (Table 5.11). There were heavy rains in the summer of 1997; in June precipitation was 67.7 mm, in July 169.3 mm, and in August 139.4 mm, and some flooding was experienced. The total amount of nitrogen released from litter in plant growth in the period March 21–October 30, 1997 was estimated at 15.33 g·m–2 or 153 kg N·ha–1, which is equal to a very high dose of nitrogen application in fertilizer. The decomposition rate was estimated by exposition of known mass of litter in mesh bags, and the rate was calculated assuming exponential decay — Wt mass of litter after t days and Wo mass at the time of exposition, t time in days. Studies on the contents of nitrogen mineral forms in the total unsaturated zone of hapludalf soils showed a constant decrease from May 26, 1997 to March 30, 1998 from 12.5 g N·m–2 to 1.4 g N·m–2. The share of N–NO3– in total mineral form appearing in the unsaturated zone was 54% in May and 66% in March. But nitrification transformations of mineral nitrogen resulted in a preponderance of N–NO3– concentrations in ground water under hapludalf soils (Table 5.12), although in the unsaturated soil zone only a slight dominance of N–NO3– was detected. The dominance of N–NO3– over NH4+ ions in ground water increased with the distance from the edge of the park indicating intensive processes of nitrification of large amounts of nitrogen released in decomposition processes, although some contribution of N–NO3– from rain was possible. Intensive nitrification was also confirmed by the decrease in organic nitrogen. However, the most important result of this study is the finding that high inputs of mineral nitrogen from decomposing organic biomass resulted in increased N–NO3– , which indicates an intensive leaching of nitrogen. Accumulation of litter can therefore convert shelterbelt from a nitrogen sink into a nitrogen source. Removal of plant debris from the shelterbelt floor is therefore needed to maintain its control functions for diffuse pollution.

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Table 5.12 Annual Mean Concentrations of N–NO3– , N–NH4+ and Organic Nitrogen (mg·dm–3) in Ground Water Seeping through Old Afforestations Calculated from Monthly Samples in 1997

Form of Nitrogen N–NO3– N–NH4+ Total mineral nitrogen Dissolved organic nitrogen

Location of Piezometers in Distance from the Field-Park Boundary (m) 0 16.5 62 5.3 3.1 8.4 7.4

6.4 3.1 9.5 5.6

14.2 2.9 17.1 4.5

Results of long-term studies in the Turew landscape recommend the following guidelines for control of diffuse pollution (Ryszkowski 1998): • The ground water table should be within the direct or indirect (capillary ascension) reach of plant root systems. • Better control efficiency is obtained when the shelterbelt is composed of multiple tree species rather than one species. • With less slope of the ground water table and hydraulic conductivity a narrower shelterbelt can be installed. • Accumulated litter in shelterbelts should be removed. • A network of shelterbelts is recommended. • Other biogeochemical barriers, such as stretches of meadows, small mid-field wetlands or ponds, riparian buffer strips, and diversified crop rotation patterns all perform functions of diffuse pollution control.

PROSPECTS FOR CONTROL OF THE DIFFUSION POLLUTION THROUGH MANAGEMENT OF LANDSCAPE STRUCTURE Diffuse pollution was recognized recently as a worldwide threat, and the need for its control is recognized in an increasing number of countries. For example, the European Union, revising its environment policy in 1996, stressed the need for a fundamental shift in its priorities from environmental protection legislation to using new policy instruments for pursuing environmental problems. One of the principal issues addressed is a clear need to tackle growing problems of ground water pollution, especially nitrate pollution of water reservoirs both underground and on the surface. Despite much environmental legislation, for example, the nitrogen directive of 1992, the success of implementation thus far is low, as 87% of agricultural area in Europe has a nitrate concentration above the guideline level of 25 mg·dm–3 and 22% surpass maximum admissible concentrations of 50 mg·dm–3 (Com 1999). In the U.S., programs aimed at controlling diffuse pollution have been proposed within the Conservation Research Program and focus on implementations of riparian forest strips (FSA 1997, Lowrance 1997).

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Various environmental policies have recommended efforts to control diffuse pollution that focus on two directions of activity. The first direction concentrates on introduction of environmentally friendly cultivation methods. Those methods should be implemented at the farm level and, for example, consist of diversified crop rotation patterns, including use of after- or before-crops (catch crops), which grow when the main crop is absent in late autumn or early spring, to reduce nitrate leaching. Other proposed methods aim at conserving soil organic matter, application of fertilizers in quantities adjusted to cultivars’ needs, integrated methods of pests and pathogens control, among others. The objective is to maintain high storage capacities of soil and to preserve or improve its physical, chemical, and biological properties in cultivated fields. But water cycling processes occur on a spatial scale much larger than the farm and waterborne migration of various chemical compounds is not restricted to one field. The meteorological conditions influencing nitrogen cycling also depend on processes occurring on regional or global scales. These constraints to efficient environmental threat control within the farm can be overcome by managing the landscape structure so as to increase its capacities for long-term nitrogen storage, recycling between ecosystems, or gas release in the form of N2. The second direction of pollution control activity consists, therefore, in introduction or manipulation of agricultural nonproductive elements of landscape to increase their protection functions. But care should be taken with regard to effects obtained. The conversion of ground water nitrogen into N2O fluxes could increase the concentration of greenhouse gases and therefore only changes the kind of environmental threat, namely, from water pollution to climate-warming phenomenon. A majority of projects for controlling diffuse pollution direct attention to implementation of riparian vegetation strips (Haycock et al. 1997). The studies carried out in the Turew landscape have shown that the upland parts of the drainage area if diversified by a network of shelterbelts or meadows can also effectively cleanse ground water of nitrogen pollution caused by modern agriculture. Although there is a consensus that vegetation strips or patches within the landscape show controlling effects on water quality, the reasons for that phenomenon are elusive. The emission of gaseous nitrogen forms in the denitrification processes is claimed to be the primary mechanism of nitrates control in the riparian buffer zones (Gilliam et al. 1986, Correll 1997, Haycock et al. 1997a, Lowrance et al. 1995). The nitrogen emissions during the denitrification processes can exceed 100 kg N·ha–1year –1 (Groffman 1997) or approximately 1 mg N·m–2 ·h–1. This general estimate includes both N2 and N2O emissions, so the comparison with nitrous oxide evolution in the Turew landscape is very rough. The average N2O evolution rate in shelterbelts during plant growth (Table 5.10) in the Turew landscape is about ten times lower than the general approximation of N2 + N2O flux from the riparian buffer zones provided by Groffman (1997). Rudaz et al. (1999) studying grasslands found that the N2:N2O ratio fluctuated strongly during the plant growing season with values ranging from 0.4 to 16.9, assuming the highest values at the time of well-developed vegetation and high content of soil water. Eichner (1990) reported that annual rates of N–N2O emissions from agricultural soils ranged, after conversion to units used in this chapter, from

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2 µg N·m–2 ·h–1 to 475 µg N·m–2 ·h–1. Kessel et al. (1993) estimated N–N2O emission rates in cultivated fields ranging from 46 µg N·m–2 ·h–1 to 904 µg N·m–2 ·h–1 during the vegetation season. In this last study, the N2 release was almost equal to N2O emissions. The emission rates estimated for cultivated fields in the Turew landscape were intermediary values (Table 5.10) with regard to the range of estimates reported by Eichner (1990) and Kessel et al. (1993). Groffman and Tiedje (1989) estimated the mean annual nitrogen loss to denitrification to be 0.6 kg N·h–1 year–1 for a well-drained, sandy forest soil and 0.8 kg N·h–1 year –1 for somewhat poorly drained, sandy forest soils. These estimates are much lower than the approximation provided by Groffman (1997) for riparian buffer zones cited above. After conversion to units enabling comparison with estimates of nitrogen fluxes found in the Turew landscape, the Groffman and Tiedje (1989) figures are equal to 6.8 µg N·m–2 ·h–1 for the well-drained soil and 9 µg for the less-drained soil under forest. These rates of N emission are very low in comparison with N2O release rates in shelterbelts. The reason for that discrepancy is unknown. The important result of our studies is the indication that shelterbelts are characterized by lower rates of N2O evolution than are cultivated fields. A shelterbelt’s efficient control of the nitrates inputs with ground water from a cultivated field (Tables 5.3 and 5.4) is not tied to increased evolution of nitrous oxide, which would be connected with stimulation of greenhouse gases. In comparison to cultivated fields, the mean rates of N2O evolution from soil of shelterbelts constituted only from 40 to 56% (Table 5.10). Although the rates of dinitrogen emissions were not estimated, shelterbelts do not clean water of nitrates at the expense of climate-warming stimulation. The rapid uptake of nitrates by plants and microbes increases the infrasystem nitrogen cycling, which builds storage capacities of shelterbelts. As was shown, the long-term storage of nitrogen in humus and tree wood is higher than is the release of nitrogen as nitrous oxide (210 µg N·m–2 ·h–1 and 97–142 µg N·m–2 ·h–1, respectively). That process is caused by slow accumulation of humus, which will probably stop in a very old shelterbelt such as occurs in old natural forest (Hedin et al. 1995). When decomposition of accumulated litter is very high, the old-growth shelterbelt turns from a sink to a source with respect to nitrogen cycling in the landscape (Table 5.12). Results of studies on afforestation in the Turew landscape support the N saturation hypothesis postulated by Omernik et al. (1981) and Aber et al. (1991). Thus, removal of litter is a very important condition for management of shelterbelts in order to implement successful control of diffuse pollution. The conversion of nitrates to ammonium due to plant and microbe metabolic processes could to some extent control nitrogen leaching. The amounts of NH4+ fixed by the soil’s cation exchange capacity prevents leaching of this nitrogen form. Nevertheless, precipitation events introducing salt solution (e.g., potassium) wash out some amounts of fixed ammonium. The contents of fixed NH4+ change after rains, therefore, but the movement of ammonium across the soil profile is delayed. The soil sorption capacities of hapludalf and glossudalf soils present in the Turew landscape are low, but accumulating organic matter under shelterbelts growing on those soils increases their sorption capacities (Pokojska 1988).

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The sharp decreases of N–NO3– concentrations in ground water passing under the biogeochemical barriers (Table 5.3) indicate that biotic demands for nitrates are high relative to supplies. Nitrogen incorporated into biomass undergoes mobilization and repeated immobilization processes linked to biological interactions between plants, animals, and microbes. Efficiency of infrasystem recycling determines dynamic storing capacities of the system, and that volume is increased with the diversity of interacting organisms. The decomposition of urea may be used as the index of the dynamic internal recycling of nitrogen. For the sake of comparison with other fluxes presented in this analysis of the biogeochemical barrier functions, the estimates of urease activity (Table 5.8) were converted into approximation of ammonia production per 1 square meter. The conversions were made using the soil bulk density estimates as well as other correction factors such as those that 1 µg of urea hydrolyzed release 0.47 µg N–NH3 ·g–1soil·h–1 (Zantua and Bremner 1977), and those connected with volumes of the sampled air. All approximations of NH3 production rates in urea decomposition were converted to the entire season means of N–NH3 produced per hour in a soil block 1 m2 in area and 0.3 m deep. In the 7- and 140-yearold shelterbelts studied, the average rate of NH3 production was 1.11 g N–NH3 ·m–2 ·h–1 and 1.64 g N–NH3 ·m–2 ·h–1, while in adjoining fields the production of ammonia assumed values of 1.3 g N–NH3 ·m–2 ·h–1 and 0.83 g N–NH3 ·m–2 ·h–1. Estimates of the season mean-production rates of ammonia were obtained by analysis of soil samples under laboratory conditions and did not reflect real soil temperatures; standard quantities of reagents were also used. Nevertheless, such approximation illustrates well the magnitude of the transformation studied. The rates of N–NH3 production in decomposition processes of urea were several thousand higher than rates of nitrogen emission in the form of N2O or nitrogen long-term storage in humus. Such a great discrepancy can be interpreted as a result of fast nitrogen recycling in the dynamic system of interactions (Ryszkowski et al. 1997, Aber 1999). The large pool of internally recycling nitrogen, which is evidenced by very high NH3 production rates, is the result of interactions among a diversified set of components. Elimination of any one functional component — for example, plants — will limit assimilatory reduction of nitrates, which in turn will decrease the volume of recycling nitrogen. The internal nitrogen recycling, which is sensitive to a set of control factors, is poorly known. The complex interactions among plants, animals, and microbes modified by physical and chemical factors should be understood before management strategies to prevent nitrogen saturation of the biogeochemical barrier could be proposed. Such knowledge may also be useful in the purposeful steering of nitrogen fluxes for different output routes from the biogeochemical barrier. Any imbalance between components of the internal dynamic system of interactions results in promoting output products such as gaseous nitrogen forms and leaching of mineral or organic forms, as well as storing capacities of the system. At present, the best guideline for efficient diffuse pollution control is to introduce a network of the biogeochemical barriers, which eliminates the temporal inefficiency of one component in the system. Thus, the network of biogeochemical barriers in the Turew landscape efficiently controls the concentration of mineral forms of nitrogen in the main drainage canal despite high input of fertilizers.

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Implementation of Riparian Buffer Systems for Landscape Management Richard Lowrance and Susan R. Crow

CONTENTS Buffers as Critical Components of Managed Landscapes....................................145 Riparian Ecosystem Functions in Agricultural Landscapes .................................148 Purposes of Riparian Ecosystem Buffers..............................................................149 Making Buffers Sustainable at Multiple Scales in Agricultural Landscapes.......150 USDA Programs for Riparian Ecosystem Buffers................................................151 Simple Decision Tree for Riparian Ecosystem Decision Making........................152 Summary ................................................................................................................155 References..............................................................................................................156

BUFFERS AS CRITICAL COMPONENTS OF MANAGED LANDSCAPES In recent years efforts have been made to incorporate a landscape perspective into U.S. national policy initiatives for land management. Supporting these efforts, landscape ecology has been regarded as an effective paradigm for organizing and evaluating various approaches to land management. In part, this reflects landscape ecology’s focus on applying principles derived from studying landscape elements, their interactions and changes over time, to solving practical problems in the real world. A fundamental premise of landscape ecology is that the pattern of component ecosystems or landscape elements affects ecological processes. Study of landscape pattern focuses on three basic landscape characteristics: structure, the spatial relationships among distinct ecosystems or landscape elements; function, the interactions

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or flows of energy, materials, and species among ecosystems; and changes in landscape structure and function over time. Within this context, landscape structure may be described as a mosaic of three elements: patch, corridor, and matrix (Forman and Godron 1986). A patch is a unit of a landscape represented by discrete areas or periods of relative homogeneity in environmental conditions, and is perceived by organisms or relevant ecological phenomenon of interest as bounded by discontinuity in environmental character. Patches are dynamic, occurring at a variety of spatial and temporal scales. Thus, a landscape is composed of a hierarchy of patch mosaics across a range of scales. Corridors are narrow landscape elements differing from their surroundings, distinguished by their linear spatial configuration in which corridor width and sinuosity are important characteristics. The landscape matrix is the most extensive and connected of the elements composing a landscape and, therefore, is functionally the most dominant landscape element. The overall pattern of landscape elements may include networks in which patch number and configuration, corridor connectivity, and boundary shapes affect flows and interactions of energy, matter, and species which is particularly relevant to riparian landscapes. It is important to note that landscape extent, as well as the area associated with each landscape element, is dependent on the organism or ecological phenomenon of interest. Therefore, there is no single definition of landscape. Rather, it is necessary to define a landscape by delineating the land area of interacting landscape elements relevant to a particular organism or phenomenon. There are at least two important implications of defining landscape in this way. The first is that scale and context are critical concerns for landscape description and management. For example, in characterizing a particular landscape, is forest the landscape matrix or is forest an element within an agricultural matrix? A second important implication relates to the degree to which the landscape may be characterized as an open or closed system. If a watershed is defined as the landscape of interest, from a hydrologic perspective at least, the landscape may be considered a relatively closed system in which few outputs leave the system. On the other hand, the system may be characterized as relatively open in terms of species movement through the system. These implications are particularly relevant to the management of landscapes containing typical agricultural production systems because of the significant inputs and outputs associated with these systems. Landscapes and elements within landscapes may be more or less intensely managed. In an agricultural landscape, for example, upland areas with fertile soils are intensely manipulated, whereas lowlands with hydric soils and streams may not be directly manipulated (though certainly they may receive significant inputs as a result of management of adjacent areas). In these intensely managed landscapes, some landscape elements may be regarded as critical to mitigate exports of other landscape components and thereby support the overall healthy functioning of the landscape system. Landscape corridors are recognized as major structural and functional components of the landscape, necessary to ecological regulatory processes such as animal dispersal, habitat for nongame species, prevention of soil and wind erosion, and integrated pest management (Barrett 1992). In addition, these landscape elements may serve to mediate or buffer the effects of outputs from other landscape

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components. In this context, riparian environments are critical components in landscapes managed for agricultural production, as well as other intensively managed landscapes. Riparian environments include those ecosystems adjacent to rivers and streams. In addition to extensive floodplains, riparian zones include narrow strips along downcutting rivers, islands, and channel landforms (Malanson 1993). These riparian systems represent ecotones between terrestrial and aquatic ecosystems and are characterized as landscape corridors in which lateral water flow is the main force organizing and regulating the function of riparian wetlands and their role in the landscape. These unique environments are of particular interest to land managers and policy makers because of the indirect, but critically important, economic benefit they serve in maintaining water quality. In particular, studies in agricultural landscapes have established the effectiveness of riparian vegetation in filtering agricultural nutrients and trapping agricultural sediments. U.S. agricultural policy has designated riparian buffer zones as eligible for inclusion in the U.S. Conservation Reserve Program, allowing farmers to be paid not to farm these environmentally sensitive lands if forest vegetation is regenerated either through planting or succession. Agricultural production systems are inherently “leaky” for nutrients, sediment, and agricultural chemicals. The degree of “leakiness” is generally measured by comparing agricultural systems to nonagricultural systems, typically forested landscapes in humid regions. The leakiness is caused by numerous interacting factors, including (1) tillage to produce seedbeds and control weeds; (2) application of nutrients from fertilizer and manure; (3) application of xenobiotics to control pests; (4) hydrologic modifications of drainage systems to remove excess water; and (5) application of water to the root zone to relieve soil moisture deficits. Buffer zones, established as landscape corridors in agricultural systems and existing as integral landscape elements in agricultural watersheds and other landscapes, primarily have been implemented to control the unplanned leaks from agricultural management systems before they impact adjacent terrestrial, wetland, and aquatic ecosystems (Lowrance et al. 1997). In addition, as discussed above, buffers are needed in agricultural landscapes to serve other landscape functions such as wildlife habitat, visual screens, and as setbacks from vulnerable ecosystems. In addition to the more conventional view of buffers as primarily linear ecosystems or ecotones juxtaposed between vulnerable ecosystems and an agricultural production system, it is also useful to consider agriculture and buffer systems in a more general way. Applying the concept of a buffer as any less intensively managed portion of a landscape producing fewer external outputs than other landscape components, agriculture may serve as a buffer. For instance, in urbanizing landscapes, agriculture may serve as a transition between high density developments with a significant percentage of impervious surfaces and nearby naturally functioning ecosystems. This is the case for many areas at the edge of urban sprawl and is one of the primary motivations for preserving agricultural lands for open space. The emphasis at the edge of urban areas should be on preserving agricultural land that can contribute to food supply for the urban centers. Conversely, when agriculture is the most intensive land use in a landscape, the nonagricultural landscape elements serve as parts of the general buffer system supporting sustainability of the entire landscape.

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This situation is especially true in ground water-dominated landscapes where most lands are equally likely to provide recharge to ground water. In these sorts of systems, water quality problems from agricultural production systems often may be avoided by having a substantial part of the landscape in nonagricultural uses.

RIPARIAN ECOSYSTEM FUNCTIONS IN AGRICULTURAL LANDSCAPES Riparian ecosystems originally referred to streamside or riverside ecosystems that developed due to the influence of the stream itself. The definition has now been expanded to include almost any land adjacent to a freshwater system, including ponds, lakes, ditches, and canals. As has been documented in numerous reports, riparian ecosystems control many of the interactions among terrestrial and aquatic ecosystems. Most receive subsidies in the form of water and nutrients from adjacent uplands. Many are flooded periodically, but whether the flood acts as a subsidy or not is a function of how often it is flooded and the severity of the flood. In areas of infrequent scouring floods, the flood acts less as a subsidy and more as a perturbation to produce new flow channels and to reset both soil and vegetation succession of the systems. Although riparian systems are usually considered primarily as horizontally connected to the stream and upslope ecosystems, there are also important vertical connections with the hyporheic zone beneath the stream. This point is of particular importance in regions where the hyporheic zone consists of gravel and coarser materials and where there are large interstitial spaces for water and organisms. Although typically referred to as ecosystems, riparian zones actually form ecotones between terrestrial and aquatic ecosystems. They may or may not be wetlands, depending on both frequency and duration of flooding and hillslope hydrology. Floodplain wetlands tend to develop in the riparian zone along larger streams and rivers, while seepage wetlands tend to develop at the base of hillslopes along smaller streams. As a result of their position in the landscape, riparian ecosystems often serve as natural buffer zones. Most riparian ecosystems serving as buffers in agricultural landscapes are functioning essentially as natural buffers with very little management. Most riparian buffers that have been studied, and that form the basis for our knowledge of buffer system functions, are naturally occurring ecosystems that developed over time as forests were converted to agricultural landscapes (Jacobs and Gilliam 1986, Lowrance et al. 1984, Peterjohn and Correll 1984). The water quality functions of these naturally occurring buffers have been summarized in numerous reviews and are represented from most to least general in Figure 6.1 (Lowrance et al. 1997). We have just recently begun to consider both the management and reestablishment of riparian buffers where they are not functioning adequately or where they do not exist (Schultz et al. 1995, Vellidis et al. 1993). The design of riparian buffer systems for agricultural landscapes is in its infancy. Although it is theoretically possible to design buffers that have a very high capacity to filter pollutants, it is not clear that these buffers will maintain this function long term.

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Control Aquatic Environment Remove sediment & sediment bound chemicals Remove nitrate from groundwater Remove dissolved phosphorus Figure 6.1

Most general to least general water quality functions.

PURPOSES OF RIPARIAN ECOSYSTEM BUFFERS Whether we realize it or not, we expect and receive numerous goods and services from natural riparian ecosystems. We do not yet know which of these goods and services may be sustained from restored or established riparian ecosystems. Natural riparian ecosystems provide, at least, the following goods and services: retain sediment; retain dust and windblown particles, including plant propagules; retain and transform nutrients; retain and transform toxics; shade streams and margins of rivers and lakes; provide leaf litter and woody debris as energy sources; provide woody debris as substrate and channel structures; provide sources of biodiversity; increase micro-topographic variability; provide carbon sinks; provide energy sinks, especially for moving wind or water; provide sources of plant propagules; provide terrestrial wildlife habitat; provide products such as wood and forage; and provide recreation, hunting, and landscape aesthetics. As fundamental components of agricultural landscapes, riparian buffers mitigate off-site effects of production systems, including increased nutrient, sediment, and pesticide loading. Agricultural landscapes, especially annual crops, decrease permanent cover, wildlife habitat, and biodiversity, and they create undesirable habitats for noncrop species. Buffers protect critical areas, including wetlands, recharge areas, aquatic ecosystems, and endangered species habitat, and link landscape components, providing corridors between critical areas and less disturbed areas. Buffers also may decrease the intensity of agricultural production at the edges of critical areas. Riparian buffers provide specialized features for human use in managed landscapes, including recreation, woodlots, and aesthetic experiences. In a sense, riparian buffers serve as insurance to protect critical areas from both unexpected and expected external effects of production systems. The expected effects of production systems depend largely on the intensity of production and the extent to which production systems dominate more natural systems. As noted above, if the landscape matrix becomes agriculture, there are generally more expected effects from the production system than if the matrix retains more of the character of natural systems with agriculture located in the landscape on the most productive soils. In countries practicing modern production agriculture, emphasizing water and environmental quality best management practices, some have questioned why buffers

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would be needed for specific purposes such as nitrate removal. It is reasoned that we now have the ability to keep chemicals applied where they belong in the landscape to enhance crop production, and if we do that buffers are not needed to control these chemicals. In short, we are capable of controlling crop production chemicals on site; therefore, buffers are not required for their management. There is no doubt that keeping chemicals where they belong, in the root zone or in plants, is the best way to achieve water quality goals in agricultural landscapes. At doubt is our ability to do this with the consistency needed to protect the environment. At this point, what are expected effects and what are unexpected effects become relevant questions. As long as we continue to till the soil, and use large amounts of nutrients and xenobiotic chemicals, and cannot control the weather, conservative management practice requires us to assume that the expected effects of agriculture will be soil, nutrient, and chemical movement significantly beyond both the background from natural ecosystems and the ability of aquatic ecosystems to assimilate and process. Given these conditions, implementing a combination of buffer systems and proper field management will provide both the best regional environmental quality and ecologically sustainable agriculture.

MAKING BUFFERS SUSTAINABLE AT MULTIPLE SCALES IN AGRICULTURAL LANDSCAPES The goal of establishing buffer systems integrated with conservation practices in agricultural production areas is to ensure sustainable, productive landscapes. Buffers mainly contribute to ecological sustainability (Lowrance et al. 1986) but may also contribute to economic sustainability. Three biophysical factors influence the ability of buffers to contribute to ecological sustainability: size, time, and management. The ecological sustainability of the buffer systems, and in turn the ecological sustainability of the agricultural landscape, ultimately will be governed by properties of the buffer systems interacting with properties of the production system. Given the linear nature of riparian ecosystems, size involves both the linear extent along a stream and the width of the buffer relative to specific pollutant sources. Size matters in riparian ecosystems. Although it is clear that a continuous buffer is best, it is not clear that there is an optimum buffer width, given the opportunity costs associated with buffers relative to other more economically important land uses. Simulation studies using the Riparian Ecosystem Management Model have shown that most sediment and nutrient removal occurs in about 15m riparian buffer systems in the U.S. Coastal Plain (Williams, et al. 2000). The generality of these results needs to be tested in other regions. In the absence of government subsidy, optimum buffer width, although lacking more specific definition, is the minimum width that provides a desired control of pollutant externalities (both a societal and local benefit) and provides other amenities desired by the landowner (primarily a local benefit). Time required to establish buffer function also is variable, but it is likely to be short in most areas. In areas of minor modification, such as a cut-over riparian forest, many of the soil and hydrologic functions are still in place and vegetation will often re-establish rapidly (Vellidis et al. 1993). In areas of major modification, such as

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streamside fields, establishing a buffer will be a very large change in chemical loading, tillage, etc., and establishment of buffer functions should be rapid relative to the agricultural uses. Even in areas of surface drainage with ditches, providing coarse woody debris to the stream in the first few years of buffer establishment should have effects on flow regimes. The three agricultural scenarios most likely to need longer time to re-establish buffer functions are areas with extensive subsurface drainage, areas with intensive streamside use by domestic animals, and steep areas with eroded soils. Managing riparian buffers for multiple benefits is a new concept in modern production agriculture. Although one approach to buffer design for pollution control allows intensive management to be substituted for size, this may not be a realistic approach in practice. Although many farmers may spend noncritical times (especially winter) managing buffer areas for multiple benefits (especially as wood lots and wildlife habitat), managing buffers for pollution control during the growing season will not be a high priority for most farmers. Active growing-season buffer management is probably not a realistic expectation for most modern farmers. Therefore, buffers should be largely self-regulating, be highly resistant to failure during the growing season, and be suitable for largely nongrowing season management. To date, riparian buffers have been implemented largely on a field-by-field basis. Future efforts should establish and evaluate riparian buffers at multiple spatial scales. At the field scale, it is possible to adjust inputs and management to gain desired outputs. Where there are likely to be greater outputs from a given field, for instance an area in intensive vegetable or animal production, the farmer may implement a larger riparian buffer to interact with in-field buffers such as contour filter strips or grass waterways. At the farm-scale, the goal should be to integrate production components where possible — rotations, animal manures, agroforestry — to buffer critical areas on and adjacent to the farm. At the landscape scale, practices should be coordinated to buffer and protect critical areas and link habitat resources with buffer systems serving as landscape corridors. In most cases, it will be possible to restore critical areas only through such coordinated efforts.

USDA PROGRAMS FOR RIPARIAN ECOSYSTEM BUFFERS Riparian buffers are an important part of the USDA Conservation Buffer Initiative (CBI), intended to have 2 million miles of total buffers installed by the year 2002. Although the CBI includes many types of buffers, the focus of CBI financial incentive programs has been to provide financial support for long-term riparian forest buffers through the USDA Conservation Reserve Program (CRP) and the Conservation Reserve Enhancement Programs carried out as state/USDA partnerships. Riparian forest buffers are the primary practice implemented under the Continuous Sign-up of the CRP (CS-CRP) which allows landowners to offer eligible acreage at any time. Eligible acreage includes cropland along streams with a cropping history in 3 out of the 5 most recent years or pastureland that is along streams (FSA 1997). As with other CRP programs, the CS-CRP provides either 10- or 15-year annual rental contracts between USDA and landowners. Unlike other CRP programs, CS-CRP for

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riparian forest buffers provides a one-time sign-up bonus and increased cost-share for installation of the practice. With the extra incentives, there is very little initial cost to the landowner. A comparison of the use of riparian forest buffers under CS-CRP in two states provides insights into both the need for riparian forest buffers and the effectiveness of USDA financial incentives for them. Iowa has extensive acreage of cropland along streams and rental rates for CS-CRP land is from $150 to $175 per acre per year. Georgia has much less row cropland along streams, more pastureland along streams, and lower rental rates for riparian lands, typically $40 to $50 per acre per year. Rental rates for both states are based on soil productivity for typical riparian soils. The difference in rental rates is reflected in dramatic differences in both the overall use of riparian forest buffers under CS-CRP and the distribution of new riparian forest buffers under CS-CRP within the two states. From October, 1999 through April, 2001, over 22,500 acres of riparian forest buffer were installed under CS-CRP in Iowa (USDA-NRCS-PRMS 2001). In contrast, only 1586 acres were installed under CS-CRP in the same time period in Georgia (USDA-NRCS-PRMS 2001). The distribution of CS-CRP riparian forest buffers in the two states is very different also. In Iowa, CS-CRP riparian forest buffers are being installed in the majority of counties. Although counties in the more humid eastern part of the state have higher acreages, the practice is widespread under CS-CRP (Figure 6.2). In Georgia, the practice is much less widespread geographically with the limited acreage concentrated in a few counties (Figure 6.2). Of the total CS-CRP riparian forest buffer acreage in Georgia, 70% has been installed in five counties (out of 163 counties total) with 38% in one county. Although the CS-CRP recognizes the value of riparian buffers by providing for continuous sign-up, the rental rates are tied to the agricultural productivity of the land based on the soil type. This is a relatively successful approach in cases where riparian soils are supporting productive croplands because the rental payment is relatively high. However, where riparian soils are supporting pastures, and the soil productivity is generally low, the program has not been as successful in re-establishing riparian buffers. Yet many streams in Georgia are impaired due to low dissolved oxygen and high fecal coliform levels (SRWMD, 2000). Although cause and effect are not well understood, both low dissolved oxygen and high fecal coliform may be related to streamside pastures. These conditions indicate that some important benefits to society are not being realized in CS-CRP riparian forest buffers on pasturelands, and they suggest that adjusted rental rates might better capture the overall societal values of riparian forest buffers. At this point, one of the most pressing concerns for CS-CRP is to acquire more riparian pastureland for permanent riparian forest buffers.

SIMPLE DECISION TREE FOR RIPARIAN ECOSYSTEM DECISION MAKING The functions of riparian ecosystems relate to their current conditions, as well as to societal goals and landowner goals. A few simple decision trees will be used

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Figure 6.2

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Comparison of Georgia and Iowa riparian forest buffer acres enrolled in the USDA Conservation Reserve Program from October 1999 to April 2001.

here to illustrate possible interactions between riparian ecosystem conditions and human goals to guide buffer design at a site or field scale. If riparian systems are largely intact, the goal will be to use and enhance existing riparian ecosystems (Figure 6.3). Unfortunately, incentives generally are not available to preserve existing riparian ecosystems. A few regulations exist, especially for wetlands, but programs are needed to reward landowners for maintaining riparian systems. In many cases, riparian systems could be enhanced for multiple purposes via species enrichment, restocking, etc. However, very limited financial incentives are available for these practices. If current conditions include degraded riparian systems with minor hydrologic modification, controlling nonpoint source pollution and restoring aquatic ecosystems should be relatively straightforward (Figure 6.4). Controlling nonpoint source pollution probably could be accomplished with any perennial vegetation; however, restoring aquatic ecosystems will require native vegetation. Although USDA programs have a default minimum buffer width of 15 m, this minimum is not well

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Primary Goal: Control Nonpoint Source Pollution Secondary Goal: Restore Aquatic Ecosystems

Use Existing Riparian Ecosystems Preserve through incentives and/or regulations Figure 6.3

Enhance through species enrichment, restocking, etc.

Simple decision tree for riparian ecosystem selection — natural riparian ecosystems in place.

Primary Goal: Control Nonpoint Source Pollution Secondary Goal: Restore Aquatic Ecosystems

Establish productive system of perennial vegetation Determine minimum distance default=15 m Figure 6.4

Determine Landowner preference of vegetation

Restore native vegetation for secondary objective

Simple decision tree for riparian ecosystem selection — degraded riparian ecosystems, minor hydromodification.

Primary Goal: Restore Aquatic Ecosystems Secondary Goal: Terrestrial wildlife

Establish native perennial vegetation Determine minimum distance default=5 m Figure 6.5

Determine Native vegetation

Restore much wider buffer for secondary goal

Simple decision tree for riparian ecosystem selection — degraded riparian ecosystems, minor hydromodification.

tested. Practices implemented beyond the minimum distance for cost-share programs such as CS-CRP will depend on landowner objectives. Given the same existing situation described above — degraded riparian systems and minor hydromodifications — restoring aquatic ecosystems and terrestrial wildlife will require a wider buffer (Figure 6.5). The default minimum distance for restoring aquatic ecosystems is only 5 m for USDA approved buffers, but, if terrestrial habitat is a secondary goal, up to 100 m of perennial native vegetation is likely

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Primary Goal: Terrestrial Wildlife Habitat Secondary Goals: nonpoint source pollution & aquatic ecosystem

Establish native perennial vegetation Determine minimum distance default=100 m Figure 6.6

Determine Native vegetation

Secondary objectives met with wildlife buffer

Simple decision tree for riparian ecosystem selection — degraded riparian ecosystems, minor hydromodification.

Terrestrial Wildlife Habitat Minimum = 100m Control Nonpoint Source Pollution Minimum= 12m Restore Aquatic Ecosystems Minimum = 5m Figure 6.7

Hierarchy of widths, based on minimal science.

needed. Alternatively, if restoring terrestrial wildlife habitat is the primary goal, it is likely that all other objectives will be met as secondary goals (Figure 6.6). The decision tree in Figure 6.7 reflects a hierarchy of buffer widths for achieving different riparian ecosystems functions. Although not well tested, the hierarchy is being implemented in USDA programs. Overall experience has shown that most landowners establishing and maintaining riparian buffers in agricultural landscapes are interested in buffers much wider than the minimum requirement. In general, the first landowners participating in these programs are ones with broader stewardship goals and desire to provide for terrestrial wildlife needs, as well as nonpoint source pollution control and aquatic ecosystem restoration. When wildlife management goals are met, it is almost certain that pollution and aquatic restoration goals also will be met, if they can be met. In reality, the nonpoint source pollution goal, especially relative to nitrate and dissolved phosphorus, probably is less certain to be met and depends on hydrologic flow paths that are unknown for most systems.

SUMMARY In general, resource-intensive land use needs buffers of less resource-intensive land use to protect adjacent ecosystems. In agricultural landscapes, even if farmers

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implement best management practices associated with modern production agriculture, buffer systems are needed to protect water quality and meet multiple other objectives in agricultural landscapes. Riparian forest buffers provide a large number of local and societal benefits in agricultural landscapes. Different riparian forest buffer widths may be applied to achieve different management objectives, although overall stewardship goals are probably most important to the majority of landowners participating in USDA buffer programs today. Differences in the adoption of riparian forest buffers in different parts of the U.S. are related to rental rates and to the need for buffers. Iowa, with larger financial incentives to enroll lands as riparian forest buffers in the USDA Conservation Reserve Program, has much greater participation than Georgia, a state with lower financial incentives in the same program. It is likely that rental rates based on soil productivity do not capture the entire suite of societal values derived from riparian forest buffers on marginal pastures and lower productivity soils. Larger financial incentives are needed to enroll riparian lands that are not highly productive for agriculture into the programs. In addition, new incentive programs are needed to reward good stewardship of existing riparian buffers.

REFERENCES Barrett, G.W. 1992. Landscape Ecology: Designing Sustainable Agricultural Landscapes, pp. 83–103, in Integrating Sustainable Agricultural, Ecology, and Environmental Policy, R.K. Olson (Ed.). The Haworth Press, Binghamton, NY. 161 pp. FSA. 1997. Farm Service Agency Handbook 2-CRP (Revision 3). USDA-Farm Service Agency, P.O. Box 2415, Washington, D.C. 20013-2415. Forman, R.T.T. and M. Godron. 1986. Landscape Ecology. John Wiley & Sons, New York. 619 pp. Jacobs, T.J. and J.W. Gilliam. 1985. Riparian Losses of Nitrate from Agricultural Drainage Waters. J. Environ. Quality 14:472–478. Lowrance, R., R. Todd, J. Fail, Jr., O. Hendrickson, Jr., R. Leonard, and L. Asmussen. 1984. Riparian forests as nutrient filters in agricultural watersheds. BioScience 34: 374–377. Lowrance, R., P.F. Hendrix, and E.P. Odum. 1986. A hierarchical approach to sustainable agriculture. Am. J. Alt. Agric. 1:169–173. Lowrance, R., L.S. Altier, J.D. Newbold, R.R. Schnabel, P.M. Groffman, J.M. Denver, D.L. Correll, J.W. Gilliam, J.L. Robinson, R.B. Brinsfield, K.W. Staver, W. Lucas, and A.H. Todd. 1997. Water quality functions of riparian forest buffers in the Chesapeake Bay Watershed. Environ. Manage. 21:687–712. Malanson, G.P. 1993. Riparian Landscapes. Cambridge University Press, Cambridge, U.K. 296 pp. Peterjohn, W.T. and D.L. Correll. 1984. Nutrient dynamics in an agricultural watershed: Observation on the role of a riparian forest. Ecology 65:1466–1475. Schultz, R.C., J.P. Colletti, T.M. Isenhart, W.W. Simpkins, C.W. Mize, and M.L. Thompson. 1995. Design and placement of a multi-species riparian buffer strip system. Agroforestry Syst. 31:117–132. USDA-NRCS-PRMS. 2001. Products — Conservation treatments. http://sugarberry.itc.nrcs. usda.gov/Netdynamics/deeds/index.html Vellidis, G., R. Lowrance, M.C. Smith, and R.K. Hubbard. 1993. Methods to assess the water quality impact of a restored riparian wetland. J. Soil Water Conserv. 48:223–230.

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Welsch, D.J. 1991. Riparian Forest Buffers. USDA-Forest Service Publ. No. NA-PR-07-91. Radnor, PA. 20 pp. Williams, R.G., R. Lowrance, and S.P. Inamdar. 2000. Simulation of nonpoint source pollution control using the riparian ecosystem management model. In Proceedings Riparian Ecology and Management in Multi-Land Use Watersheds. American Water Resource Association, Middleburg, VA, pp. 433–438.

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CHAPTER

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Dissolved Organic Substances in Water Bodies of Agricultural Landscapes Barbara Szpakowska

CONTENTS Introduction............................................................................................................159 Terminology and Methodology .............................................................................160 Source and Origin of Dissolved Organic Substances...........................................161 Concentrations of Dissolved Organic Substances in Waters ................................161 Humic Substances in Aquatic Environments ........................................................164 Amounts of Humic Substances in Ground Waters ...............................................164 Amounts of Humic Substances in Surface Waters ...............................................165 Concentration of Polysaccharides and Polypeptides in Water .............................170 Effect of Meadow Width on Humic Substances Concentration in Dry Years .....171 Effect of Meadow Width on Organic Substances Concentration in Wet Years.....172 Effect of Humic Substances on Heavy Metals Speciation ...................................173 Total Concentration of Heavy Metals in Natural Waters .....................................174 Concentration of Different Forms of Metals ........................................................176 Association of Metal Ions with Humic Substances in Natural Water..................177 The Effect of Meadow Belt on Heavy Metal Speciation .....................................179 Conclusion .............................................................................................................180 References..............................................................................................................180

INTRODUCTION In agricultural watersheds large amounts of nutrients are usually leached from cultivated fields. Increased application of commercial fertilizer has resulted in elevated concentrations of contaminators. Among water contaminators, concentrations

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of nitrates and pesticides are most frequently subjected to analysis since the presence of these components in water supplies constitutes a direct threat to human health. Long-term studies on landscape ecology carried out by the Research Centre for Agricultural and Forest Environment in Poznan´ have indicated that the spatial pattern of landscape elements can modify migration of mineral components. By restructuring uniform field landscapes into mosaic ones through installing biogeochemical barriers such as shelterbelts, meadows, small ponds, and other nonagricultural components, it is possible to decrease the output of phosphates and nitrates from a watershed (Ryszkowski 1994, Ryszkowski et al. 1997). On the other hand, there is little data on the leaching and migration of dissolved organic matter (DOM) in waters situated in agricultural areas. Recent studies indicate a quite disturbing phenomenon of growing concentrations of DOM in ground and surface waters. DOM ought to be analyzed not only because of elevated concentrations in water but also because the organic compounds, mainly humic substances (HS), are able to bind and distribute various toxic organic and inorganic compounds. In the presence of HS, precipitation of some nutritionally important anions, such as phosphates, is delayed or modified (Jansson 1998). Dissolved HS are also carriers of toxic organic compounds such as aromatic polycyclic hydrocarbons with carcinogenic activity. These compounds are adsorbed on humus surfaces or react with humus (Meyer 1990). Binding of metal ions by HS through the process of complexing or chelating seems to be one of the important properties of HS. As a result of this process, the geochemical mobility of metals, particularly of heavy metals, is changed. HS binding of heavy metals into metal-organic complexes increases their solubility, which results in higher amounts of heavy metals dissolved in water. In the presence of HS, toxicity of trace heavy metals decreases and availability of trace elements necessary for proper functioning of water organisms increases.

TERMINOLOGY AND METHODOLOGY Organic substances in water can be divided according to fraction of dissolved organic carbon (DOC) and particulate organic carbon (POC). DOC and POC may be used to monitor seasonal inputs of plant and soil organic matter to streams and rivers. For example, the melting snows of spring leach carbon into water, increasing DOC. During the summer, algal growth combined with decreased discharge increase the concentration of DOC (Thurman 1985). DOC is chemically more reactive because it is a measure of individual organic compounds in a dissolved state, while POC is both discrete plant and animal organic matter and organic coatings on silt and clay. The main obstacle encountered in studies on organic substances dissolved in water is the lack of precise and direct methods for quantitative estimations. Even in the 1970s, the most common methods were qualitative estimations of organics in water by chemical oxygen demand or oxidation by permanganate. These methods had many limitations, the most important of which was insufficient organic substance oxidation and/or interaction of ions, compounds, and particulate material. Now DOC

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is determined by oxidation to carbon dioxide and by measurement of carbon dioxide by infrared spectrometry. Decomposition of DOC, principally by microorganisms, is a dynamic and important process in aquatic ecosystems. In the case of POC, both animal decomposition and microbial decay occur simultaneously (Thurman 1985). Organic matter dissolved in water constitutes 60 to 90% of organic substances in natural waters.

SOURCE AND ORIGIN OF DISSOLVED ORGANIC SUBSTANCES Organic substances dissolved in water can be categorized according to origin: autochtonous (e.g., originating in the aquatic environment) and allochthonous (e.g., from land, or outside the aquatic system). There are two sources of allochthonous organic carbon: soil and plants. In the aquatic environment algae are the major source of autochthonous organic matter. Algae do excrete DOM, probably as a result of cellular destruction or lysis, and this DOM is actively metabolized by heterotrophic bacteria. Another important source of autochthonous organic matter is excretion of organic compounds by animals. Ruptured cells of algae or other aquatic organisms release compounds that undergo further biogeochemical degradation and mineralization. Some of them, as a result of condensation, form macromolecules. High molecular compounds of autochthonous origin are mainly polysaccharides and polyamides, a product of phytoplankton decomposition (Meyer 1990). Streams and rivers have allochthonous organic matter from both plants and soil as a major source of their organic matter. Lakes contain considerable amounts of autochthonous organic matter which may range from 30% for lakes with inputs from rivers flowing through and high flushing rates, to nearly 100% for eutrophic lakes fed by ground water. The larger the lake the more important autochthonous input of organic matter is thought to be (Thurman 1985).

CONCENTRATIONS OF DISSOLVED ORGANIC SUBSTANCES IN WATERS Concentrations of dissolved organic substances in ground waters change significantly. In some ground waters, concentrations of DOM are below 2 mg·dm–3 (Gaffney et al. 1996). Concentrations of DOM in ground waters are small because those compounds are quickly decomposed. Organic carbon is a good energy supply for heterotrophic microbes in the ground water. Moreover, organic carbon adsorbs onto the surfaces of the aquifer materials, where it is chemically and biochemically degraded and removed as carbon dioxide. Investigations carried out in the Wielkopolska Lowland-Turew landscape (Poland) indicated that concentrations of DOM strongly depend on the type of water and time of water sampling (Table 7.1). During periods of high water content in

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Table 7.1

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Estimation of DOM Concentrations in Waters of Agricultural Area in the Turew Landscape [mg·dm–3]

Period

Mean Concentration

Ecosystem

References

Ground Water 1987–1989

1990–1991

1993 1995 1996 1998

Under Under Under Under Under Under Under Under Under Under Under Under Under

field meadow meadow on slope shelterbelt field meadow meadow field meadow field meadow field field

22.4 31.1 41.4 31.2 43.6 28.9 24.3 34.2 44.7 10.5 19.4 18.3 10.5

Szpakowska and · Zyczyn´ ska-Ba l oniak (1994)

Szpakowska (1999)

Szpakowska and · Zyczyn´ ska-Ba l oniak (1996) Szpakowska and Karlik (1996) Karlik et al. (1996) Karlik and Szpakowska (2001)

Surface Water 1987–1989

Pond

47.6

1990–1991 1993–1994

1997

Canal water (1.5-m width) Drainage canal Pond Lake water Mid–field pond Model reservoir Drainage canal Melioration ditch Drainage water Pond Pond

48.7 48.7 46.1 22.7 42.6 19.8 24.8 51.2 17.7 19.7 26.0

1998

Small pond

38.2

1995

1996

Szpakowska and · Zyczyn´ ska-Ba l oniak (1994) Szpakowska (1999) Szpakowska (1999) Szpakowska and Karlik (1996)

Karlik et al.(1996) Karlik and Szpakowska (1997) Karlik and Szpakowska (2001)

soils, concentrations of DOM are also very high, confirming phenomena observed by other authors (Meili 1992). The study area of the Turew landscape was an agricultural drainage basin with an area of 11 ha, divided into two parts: area A included a small, field pond, surrounded by a narrow belt of meadow where wells were installed, and area B included a drainage canal, starting from the pond in area A, and a wide belt of meadow separating the canal from cultivated fields. The soils, consisting of hapludalfs originating from boulder clay (rich in calcium carbonate) covered by a layer of light clayey sand. Concentrations of DOM in examined waters in area A were very high, and during some periods in ground water under fields they amounted to 22.4 mg·dm–3 and in ground water under meadow 31.1 mg·dm–3, whereas in area B these concentrations were 43.6 and 24.3 mg·dm–3, respectively (Table 7.1).

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Surface waters of the Turew landscape also contained high concentrations of DOM (Table 7.1). Mean concentration of DOM in water of the mid-field pond in dry years amounted to 47.6 mg·dm–3. Strong influence of precipitation on DOM concentration in the pond water was observed (r = 0.44; p = 0.04), which indicated the input of DOM from surrounding areas. Flushing of soil and plant organic matter by precipitation caused the observed increase in DOM. Moreover, high concentrations of DOM in analyzed water were due to the location of the pond in the natural depression into which surface runoff was collected. Additionally, increased DOM concentrations may be caused by decomposition of dead plants in the pond, as well as excretion of DOM by living macrophytes. According to Meyer (1990), excretion of DOM by living macrophytes (often neglected in quantitative estimations of DOM) is substantial. Also, Rutherford and Hynes (1987) noted increase of DOM concentrations in waters situated in agricultural areas as an effect of intensive primary production of algae. Influx of DOM to the pond through ground water can also be an important element in the total carbon budget. Inflow of ground waters can modify DOM concentrations in surface waters by dissolution of DOM. Removal of organic substances from surface waters as suspended sediment also occurs (Rutherford and Hynes 1987). In agricultural areas drainage channels also contain high concentrations of DOM (Table 7.1). The average concentration of DOM in a small channel situated in the examined area was 48.7 mg·dm–3. Seasonal concentrations of DOM varied greatly. In summer this concentration rose to 104.3 mg·dm–3, whereas during spring it declined, which can be related to a dissolution effect from intensive spring rainfall and snowmelt. Maximum concentrations of DOM that occurred in the summer may result from decomposition of biomass, which is most intensive in summer. Other authors also indicated a strong relationship between precipitation and DOM concentration. Lush and Hynes (1978) noted that not only rainfall but also snow, thaw, and leaf input may be of some importance to organic carbon budgets. Moreover, aquatic macrophytes, which consist mainly of cellulose, are degraded and in autumn contributed to the increase of DOM concentrations. Release of organic carbon by macrophytes and algae caused a high concentration of DOM, which is well documented in the literature (Meyer 1990). Huge fluctuations in concentration of DOM observed in these investigations in winter can be related to freezing and thawing. Frozen soil hinders quick DOM inflow, and ice cover limits microbial activity. Irregular melting processes intensify influx of DOM and occasionally increase DOM concentrations. Apart from microbial activity having strong influence on DOM concentrations, Muenster (1992) also found adsorption of organic compounds on clay minerals when there is slow inflow and weak water mixing. Because of accumulation of organic compounds in the drainage channel, their free migration in the agricultural area is hindered, and this process plays an important role in matter cycling and transformation. The study carried out in L˛eczyn´ sko-W l odawski Lake District (Misztal et al. 1997) indicated that lake and ground waters located close to fields contained similar concentrations of dissolved organic compounds, ranging from 6.7 to 8.1 mg·dm–3. Górniak (1996) examined concentrations of DOM in water of the Siemianówka reservoir and found that a characteristic feature of this reservoir is a high concentration

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of dissolved organic carbon (mean 22.5 ± 9.6 mg·dm–3), probably the highest among the retention reservoirs in Poland that are situated in less modified forest-meadow catchment. During the year the highest DOM concentrations were observed in May, and concentrations then gradually decreased to a low in winter. The amounts of DOM in this water were directly proportional to the flushing effect and were inversely proportional to the rate of water exchange in the reservoir. Comparisons of surface, subsurface, and ground waters in south-central Minnesota, done by Maier et al. (1976), show that organic C concentrations are highest in surface waters. During May and June, organic C levels in river water were 5 to 17 mg·dm–3, whereas subsurface water had 1 to 6 mg·dm–3 organic C level and ground water had less than 2 mg·dm–3. These results indicated that organic materials were decomposed or retained in the upper layers of the soil, and that residence time in the aquifer facilitates removal of trace organics by geochemical and biochemical processes. The most likely explanations for the presence of high organic C concentrations in surface waters are carbon’s solubilization from humified soil organics and biodegradation of vegetation and animal tissues in stream channels or at the soil surface.

HUMIC SUBSTANCES IN AQUATIC ENVIRONMENTS The main fraction of dissolved carbon in waters (50 to 75%) constitutes aquatic humic substances (HS) (Thurman 1985, Szpakowska 1999). One of the difficulties encountered in the study of HS is terminology. HS do not conform to a unique chemical entity and cannot be described in unambiguous structural terms. As a result, HS are described operationally as a mixture of such organic acids as fulvic and humic acids (Thurman et al. 1988). These terms originate in the field of soil science and determine the part of soil organic matter extracted by severe chemical treatment. It seems that it would be more reasonable to classify these aquatic materials based on chromatographic methods used to extract them from water. In recent years, it has been found that high recoveries of HS from water are possible with nonionic macroporous sorbents such as the Amberlite XAD resin series. By these resins, HS can be easily extracted from any aquatic sample: from waters with very low HS values, such as sea water or ground water, as well as from more concentrated systems (Thurman et al. 1988).

AMOUNTS OF HUMIC SUBSTANCES IN GROUND WATERS There are relatively few studies on HS in ground water (Kramer et al. 1990, Hessen and Tranvik 1998)). Low concentration of HS in ground waters (usually less than 1 mg C-dm–3) has been a major deterrent to studying them. However, with resin isolation procedures developed over 20 years, it is possible to isolate HS from ground water even though concentrations are micrograms per liter (Thurman 1985). Long-term studies carried out in the Research Centre for Agricultural and Forest Environment (Polish Academy of Sciences) in agricultural areas with intensive agricultural management indicated that ground waters in the Wielkopolska region

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· contain high concentrations of HS (Szpakowska and Zyczyn´ ska-Ba l oniak 1989, Szpakowska 1999). On the basis of rank Spearman correlation, a strong dependence of HS concentration on rainfall was indicated. It was particularly clear in ground water under fields (r = 0.45; p = 0.04). The highest HS concentrations were found in ground water under fields in summer months both in 1990 (29.8 mg·dm–3) and 1991 (44.5 mg·dm–3) (Figure 7.1). Also during these periods very high concentrations of HS in ground water under meadow were observed; HS concentration was 26.0 mg·dm–3 in 1990, and 36.9 mg·dm–3 in 1991. Leaching of organic compounds from surrounding terrain and litter during the spring flush was also observed by other authors (Thurman 1985, Easthouse et al. 1992). High concentrations of HS were observed in ground water after thaws and heavy rainfall. The highest HS values appeared in ground water not immediately after rainfall but after 2 months delay. This flush carries HS into the saturated zone of ground water and is a major contributor of organic carbon to ground water (Szpakowska 1999). Górniak (1996) studying ground waters found fluctuations in HS concentrations during seasonal sampling. The autumn-winter period was characterized by huge variability in concentrations, which was connected with a change in thermal regime and in amounts of rainfall. According to Górniak (1996), the highest HS concentrations in ground waters were observed in spring. Investigations on seasonal variations of organic substances concentration are very important for aquatic ecosystems, particularly when arable fields are close to surface waters that are recharged by ground waters. However, ground water–surface water interactions are rarely quantified, probably because of perceived difficulties in measuring seepage rates. In addition, many factors affect ground water-surface water interaction, e.g., fluctuations in hydraulic gradients near the surface, watershed morphometry, and heterogeneity of porous media near the surface.

AMOUNTS OF HUMIC SUBSTANCES IN SURFACE WATERS Small ponds and drainage canals situated in agricultural areas are poorly recognized surface reservoirs — there is a lack of water supplies assessment. Their estimation is also difficult because of the astatic character of small ponds. Examining surface waters in the Wielkopolska Lowland high concentrations of HS in the midfield pond were observed. These concentrations were 91% higher than in ground water under meadow in close vicinity of the pond and 78% higher than in ground water under field. Mean concentration of HS in the mid-field pond during the time of investigations was 34.0 mg·dm–3, which accounted for 71.4% of DOM. Using rank Spearman correlation indicated that not only the concentration of DOM but also HS were dependent on precipitation (r = 0.53; p = 0.04) (Figure 7.2). The highest HS concentrations, up to 109 mg·dm–3, were found in the pond water in August, 1991, 2 months after heavy rainfall. This finding indicated that transport via ground water but not surface runoff contributed to that increase (Figure 7.3). The examined water during this time was yellow as a result of a high concentration of humus. As the cause-and-effect relationships for rainfall and HS concentration were significant, these data were used in a modeling exercise in an attempt to establish a

VI

VII

VIII

IX

X

XI

XII

I

II

III

IV

V

VI

VII

VIII

IX

Figure 7.1

HS under field

1991 HS under meadow

[mgdm-3]

Seasonal variation in concentrations of humic substances in ground water under field and under narrow belt of meadow.

rainfall

1990

0 V

0 IV

5

10

15

20

25

30

10

20

30

40

50

35

40

70 60

45

166

precipitation [mm]

80

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167

[mgdm-3]

120

HS

90

60

30

0 0

40

80

Sum of rainfall between sampling Figure 7.2

120

[mm]

160

Relationship between humic substance concentrations in surface water of pond and intensity of rainfall in dry years. (After Szpakowska 1999.)

dynamic relationship between both variables. It was found that using a linear model, one can predict the effect of rainfall on HS concentration. The measured HS concentrations in water of the pond during 2 years, expressed as a variable in this mode, were similar to those estimated theoretically (Figure 7.4), which can be essential for prognosis of system behavior, particularly changes taking place in ecosystems (Kundzewicz et al. 1994). In comparing the concentration of HS from the analyzed pond with water exam· ined earlier from a eutrophic lake situated in the same area (Zyczyn´ ska-Ba l oniak and Szpakowska 1989), much higher concentrations of HS were found in the small mid-field pond. In the lake water, maximum HS concentration was 25 mg·dm–3. Although this lake has a broad littoral zone, the input from the littoral zone decreases when lake size increases. In water of the mid-field pond, relatively high concentrations of organic substances, particularly HS, were observed. HS do not undergo rapid changes, and their increased concentrations in the pond water can be interpreted as a result of accumulation. Because HS are resistant to microbial and chemical decomposition, they accumulate even in aerobic conditions (Gaffney et al. 1996). High increases in HS concentrations in water from the pond were observed, particularly in years with low intensity of rainfall. After drought, precipitation flushes HS into ground water, and, therefore, there is a lag in response between the rainfall and appearance of HS in the pond water. This finding was clearly confirmed by rank Spearman correlation in Figure 7.2. The maximum concentrations of these substances in pond water was 109.1 mg·dm–3 when the outflow of water to the small drainage canal in summer was stopped. On the basis of rank Spearman correlation, there was no relationship

0

10

20

30

40

50

60

70

IV

Figure 7.3

precipitation [mm]

VI

VII

VIII

1990

IX

XI

rainfall

X

XII

I

HS

II

III

TC

IV

VI

1991

V

VII

VIII

IX

0

Seasonal variation in concentrations of total carbon and humic substances in mid-field and pond water in dry years.

V

20

40

60

80

100

120

140

168

[mgdm-3]

80

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0

20

40

60

80

100

120

IV

Figure 7.4

precipitation [mm]

1990 rainfall

VIII

X

II

HS measured

XII

1991

VI

HS estimated

IV

VIII

0

Simulation of concentrations of humic substances in mid-field pond water. (After Szpakowska 1998.)

VI

20

40

60

80

100

120

[mgdm-3]

140

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DISSOLVED ORGANIC SUBSTANCES IN WATER BODIES 169

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[mgdm-3]

170

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

50

HS in canal

40

30

20

10

0 0

20

40

60

HS in pond Figure 7.5

[mgdm-3]

80

Relationship between humic substance concentrations in water of mid-field pond and drainage canal in dry years. (After Szpakowska 1999.)

between HS in pond and drainage waters, indicating independence of these analyzed waters (r = –0.016; p = 0.96) (Figure 7.5). These studies indicate that small mid-field ponds control HS flow and are a barrier preventing their free migration in the agricultural landscape. Other studies on HS also indicate an important role of ponds in accumulation of HS (particularly well-oxygenated waters) (Hessen and Tranvik 1998). Unfortunately, the number of ponds has dramatically decreased. About 80% of the small ponds in the Wielkopolska region disappeared in the 20th century. Moreover, many of the ponds that still exist have been transformed into refuse dumps, etc. Thus, very important elements of agricultural landscape are damaged.

CONCENTRATION OF POLYSACCHARIDES AND POLYPEPTIDES IN WATER In addition to HS in ground waters, concentrations of polysaccharides and polypeptides (PP) were also examined. PP concentrations were lower than HS, but they cannot be neglected. Concentrations of PP averaged 2.1 mg·dm–3 in ground water under field and 5.2 mg·dm–3 in ground water under meadow where roots reached the water table. The difference between these fractions in both analyzed waters estimated on the basis of the Wilcoxon test was statistically significant (Z = 2.8; p = 0.04). Malcolm (1985) reported that concentrations of this fraction in water he analysed was even lower, which probably resulted from strong microbial degradation because of the considerable depth of ground water and the longer residence

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time of organic compounds in ground water. Concentrations of PP do not vary seasonally. There are relatively few studies on PP in ground water. Blooming of phytoplankton in surface waters has a strong effect on PP concen· trations (Sundh and Bell 1992). In previous studies (Zyczyn´ ska-Ba l oniak and Szpakowska 1989) on dissolved organic compounds in a eutrophic lake situated in an agricultural landscape also observed variability of PP. After phytoplankton bloom the highest PP concentrations, up to 95 mg·dm–3 (average 27.0 mg·dm–3), were noted. In the studies presented, no pronounced changes in PP concentrations were found. The greatest concentrations of PP amounted to 27.1 mg·dm–3, with an average of 8.2 mg·dm–3, and this constituted 17.2% of DOM. The pond bottom was covered by vascular plants — up to 90% Ceratophyllum submersum L. It is known that if reservoirs are dominated by such macrophytes, phytoplankton appears in very low amounts. A similar phenomenon was observed in this mid-field pond. Mean concentration of PP in drainage water during wet years was much higher (11.9 mg·dm–3) in comparison with this fraction concentration in the dry season (3.7 mg·dm–3). Usually concentrations of PP do not exceed 10% of DOM (Thurman 1985). These substances easily undergo enzymatic degradation. The enzymatic hydrolysis of polysaccharides releases simple monosaccharides and oligosaccharides that are quickly utilized by microorganisms, and therefore concentrations of simple carbohydrates are very low.

EFFECT OF MEADOW WIDTH ON HUMIC SUBSTANCES CONCENTRATION IN DRY YEARS Studies of ground waters flowing through the 5- to 9-m belt of meadow carried out on area A indicated that the composition of organic compounds is altered during filtering of ground water from field through narrow meadow. There was a twofold increase in PP concentration with the flow of ground water through meadow. At the same time, a 7% fall in HS concentration in ground water under meadow was observed (Table 7.2) but the difference was not statistically significant, which suggests

Table 7.2

Changes in Humic Substances (HS) Concentrations in Ground Waters According to Width of Meadow Belt in Dry Years (1990–1991)

Area of Study Area A (narrow belt of meadow 5–9 m) Area B (wide belt of meadow 20 m)

Ground Waters Under field Under meadow Under field Under meadow

Source: Szpakowska 1999.

Concentrations of HS [mg·dm–3]

Changes of HS in %

19.1 17.8

7% decrease

14.0 6.8

52% decrease

Significant Differences (on the basis of Wilcoxon test) N = 20, Z = 1.49, p = 0.14 Difference not statistically significant N = 17, Z = 3.5, p = 0.001 Difference statistically significant

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that the narrow belt of meadow was not effective in reducing HS migration from fields. The proportion of the concentration of HS to PP in the ground water under the field was different (9.1:1) from that in the ground water under meadow (3.4:1). Studies carried out simultaneously on area B indicated that the wide belt of meadow had a strong effect on ground water chemistry. With the ground water flow through the 20-m belt of meadow, concentrations of DOM were reduced by 45%. A similar phenomenon was noted for concentrations of HS migrating with ground water from under field through the wide meadow. This decrease averaged 52% (Table 7.2). This decrease is probably related to the longer time of microbial activity and greater effect of biodegradation of organic compounds. Moreover, less leaching of HS from the upper part of meadow soil is possible and can be related to slower velocity of water flow through rusty soils. From the studies we can conclude that the narrow belt of meadow separating arable fields has an effect on composition of DOM but was not effective in limiting free migration of HS in the years with low intensity of rainfall. The wide, 20-m belt of meadow is much more effective in reducing transport of chemical compounds, particularly HS and DOM. Thus, especially in dry years, a wide belt of meadow can be an important biogeochemical barrier for controlling the spreading of chemical components from cultivated fields in ground water. Taking into consideration the disturbing phenomenon of increasingly hard-to-control nonpoint source pollution, appropriate planning of agricultural environments should include the formation of such biogeochemical barriers as meadow enclaves or small field ponds.

EFFECT OF MEADOW WIDTH ON ORGANIC SUBSTANCES CONCENTRATION IN WET YEARS The present studies indicated that there were no pronounced changes in organic compounds after ground water passed across a narrow or wide belt of meadow in wet years. The rainfall intensity in 1993 was different. The first half of 1993 had very low precipitation (total for the period was 218 mm) and a 23% reduction of HS in the ground water under the narrow meadow, as compared to the ground water under field, was observed. A more pronounced decrease in HS concentration was observed in the first half of 1993 after ground water flow across a wide 20-m meadow belt. The fall in HS concentrations was on average 35% (Table 7.3). The second half of 1993 had significantly more precipitation. Total precipitation in the second half of 1993 was 190% higher than in the first half, and there was a 29% rise in HS concentration in ground water under the narrow belt of meadow, and a 60% rise in HS concentrations in ground water under the wide belt of meadow, as compared to those in ground water flowing from under the field. Rainfall intensity was similar in both halves of 1994, a humid year. In that year, no effect of the biogeochemical barrier on the decrease in DOM and HS concentrations was observed either on area A or B. Analyzing the effect of biogeochemical barriers such as a meadow on decreasing DOM and HS concentrations in ground water passing through the meadow, it was

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Table 7.3

173

Changes in Humic Substances Concentration in Ground Waters According to Width of Meadow Belt in 1993

Area of Study Area A (narrow belt of meadow 5–9 m)

Area B (wide belt of meadow 20 m)

Concentrations of HS [mg·dm–3]

Intensity of Rainfall

Ground Waters

218 mm (I–VI)

Under field Under meadow

18.7 14.4

635 mm (VII–XII)

Under field Under meadow

11.5 14.9

218 mm (I–VI)

Under field Under meadow

31.9 20.7

635 mm (VII–XII)

Under field Under meadow

25.2 40.3

Changes in HS in %

Significant Differences (on the basis of Wilcoxon test)

23% decrease N = 5, p = 0.001 Difference statistically significant 29% increase N = 5, p = 0.47 Difference statistically insignificant 35% decrease N = 5, p = 0.001 Difference statistically significant 60% increase N = 5, p = 0.01 Difference statistically significant

Source: Szpakowska 1999.

found that the decrease in these concentrations depends not only on the width of meadow but also on precipitation (Table 7.3). A more significant decrease in organic compounds was observed in a dry period in ground water situated on area B with a 20-m belt of meadow. It was shown that in dry months the washing of organic compounds from arable fields and post-bog soils decreases, whereas in wet months the outflow of both DOM and HS from soils is much higher. According to Gron et al. (1992), about 22% of dissolved organic carbon undergoes biodegradation in ground water, and degradation of the hydrophilic fraction is even higher (27%). Inflow of ground waters can modify the concentration of organic compounds in surface waters, particularly with HS, which come, for example, from humification processes taking place in soil. Soil temperature, humidity, and aeration can also be important elements having an effect on the dissolution rate and degradation of other soil components.

EFFECT OF HUMIC SUBSTANCES ON HEAVY METALS SPECIATION Many chemical and biological properties of metals in natural waters can hardly be explained on the basis of total metal concentrations. Heavy metals are distributed over many species with different toxicities to biotic life. Today the term metal speciation is used for determination of the distribution of metal ions over different physico-chemical forms. In natural waters, physico-chemical forms of metal ions include the free (hydrated) metal ion, complexes of metal with simple inorganic

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species (such as carbonate), complexes of metal with macromolecular ligands (such as humic acids), and metal ions adsorbed on a variety of colloidal particles (for example, clay minerals). Differentiation of these forms is very important because free ionic metal is the form responsible for the metal’s biological effect, whereas total metal concentration provides no information on its toxicity and prospect for uptake because a mix of various speciation forms often has contrasting properties. For example, it is generally accepted that ionic copper is much more toxic than copper in a form bound to organic compounds (Tubbing et al. 1994). Organic compounds, mostly HS, are particularly important in speciation of metals. Because of the presence of functional groups such as carboxylic and hydroxylic, these compounds can bind large amounts of cations, modifying their availability to water organisms. Generally, there are two directions in analysis concerning speciation of metals. The first — analytical — is directed to selection of an appropriate method or technique of determination, while the second — functional — deals with the problem of explaining binding and transport of metals in the environment. Such an approach requires parallel application of separation techniques: chromatographic separation membrane techniques and nonseparation ones — ion-selective electrodes or anodic stripping voltammetry (DPASV). The DPASV method enables discrimination between electroactive forms of metals (hydrated ions, labile forms) and those that are electro-nonactive (organic complexes and colloidal mixtures) (Nürnberg 1981, Szpakowska and Karlik 1996). Determination of heavy metal forms by DPASV is possible even when they appear in very low concentration (0.05–1.0 ppb) in samples containing high concentrations of other salts, e.g., calcium or magnesium (Mart et al. 1978). Modification of the DPASV method done by Szpakowska and Karlik (1996) was the basis for presenting the analytical scheme for chemical speciation of heavy metals in natural waters. Because humic substances are a mixture of compounds it was necessary to separate them into humic and fulvic acids for further analysis. This separation was done by acid precipitation at pH 2. The results indicated that fulvic acids dominated (62.7%) in surface water, whereas in ground waters these acids constituted only 28.8% (Figure 7.6). Many more humic acids, which have strong chelating properties, were found in ground waters (71.2%) than in surface water (37.3%). In waters of the Turew landscape (particularly in the mid-field pond) situated in agricultural areas, an increase in humic acid concentrations was observed in early spring. This increase can result from freezing in winter. During freezing, when ice cover is formed, a rise in HS concentrations was observed. Increased humic acid concentration in spring in dystrophic lakes was also observed by Górniak (1996).

TOTAL CONCENTRATION OF HEAVY METALS IN NATURAL WATERS Water with a high total metal concentration may, in fact, be less toxic than water with a lower total metal concentration because metals occur in different chemical

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80 70 60 50

% 40 30 20 10 0

KF

KH

KF

ground water Figure 7.6

KH

surface water

Percent of humic acids and fulvic acids in ground and surface waters.

Table 7.4

Total Concentrations of Heavy Metals in Waters of Drainage Catchment of the Turew Landscape [g-dm–3]

Waters Examined

Zinc

Cadmium

Lead

Copper

Lake Mid-field pond Artificial reservoir Drainage canal Melioration ditch Ground water under field Ground water under meadow

123.1 92.6 61.1 87.6 145.6 57.7 132.0

0.72 0.22 0.72 0.40 0.19 0.39 0.34

10.3 13.6 5.4 13.1 7.4 4.2 7.8

28.9 8.2 22.4 14.6 16.5 25.7 21.5

Source: Szpakowska and Karlik 1996.

forms. Analyzing the total concentrations of heavy metals in the ground and surface waters of the Turew landscape, the highest mean concentrations were found for zinc (99.9 µg·dm–3), and the lowest for cadmium (0.42 µg·dm–3) (Table 7.4). The range of zinc concentrations in ground water was from 57.7 to 132 µg·dm–3 and was similar to the concentrations of this metal in the surface waters (61.1 to 145.6 µg·dm–3). The concentrations of copper and lead had intermediate values and ranged from 4.2 to 7.8 µg·dm–3 for lead in ground waters and 5.4 to 13.6 µg·dm–3 for surface waters. Comparing copper concentrations in ground and surface waters, it was found that Cu concentrations were 23% higher in ground water. Copper concentrations in surface waters differed considerably, depending on the kind of reservoir or water course (steady, running, differentiation of plant communities). The obtained values of metal concentrations in ground and surface waters were similar, which can be related to the location of the waters studied in the same agricultural water drainage basin, and similarity of the results can be related to low soil differentiation. Comparing the metal concentration estimates for the studied waters to those obtained by other authors for waters also running through farming areas, great

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Total Concentrations of Heavy Metals in Natural Waters [g·dm–3]

Table 7.5

Type of Water

Zinc

Cadmium

Lead

Copper

References

Rainfall Ground watera Mid-field ponda River water

159 1940 120 88.6

0.48 13 8 0.628

4.9 64 26 8.18

1.9 39 16 35.8

Ch l opecka and Dudka (1991) Pilc et al. (1994) Pilc et al. (1994) Golimowski and Sikorska (1983)

a

Water located in areas with high chemical soils contamination.

similarities can also be found (Table 7.5). Only in waters localized on soils considerably contaminated with dust emitted by a metallurgical industrial plant were the Pb and Cd concentrations much higher in both ground and surface waters. The heavy metal concentrations in running and stagnant waters are highly variable. Quantitative differentiation of the metals in the studied waters depends mainly on catchment area utilization as well as rate of sedimentation (Pasternak and Antoniewicz 1971, Karlik and Szpakowska 1999). As emphasized earlier, heavy metals in waters occur not only in ionic forms but also are able to create bonds with, for example, ligands such as aliphatic acids, amino acids, and other compounds.

CONCENTRATION OF DIFFERENT FORMS OF METALS Ionic forms, labile forms, and the sum of stable complexes and chelates for Zn, Cd, and Pb were determined in the surface and ground water of the Turew landscape. In both types of water, great differences in percentages of each form of the metals were noted, particularly concerning ionic forms (Tables 7.6 and 7.7). Clearly, a lower Table 7.6

Chemical Forms of Zinc, Cadmium, and Lead in Ground Water under Field

Metal Examined

Concentration [g·dm–3] Ionic Labile Stable Forms Complexes Complexes

Zinc Cadmium Lead

17.9 0.003 0.28

17.2 0.088 1.78

36.3 0.248 1.02

Ionic Forms

% of Form Labile Complexes

Remain (stable)

25.2 0.9 9.1

24.1 25.9 57.8

50.8 73.2 33.1

Source: Szpakowska and Karlik 1996.

Table 7.7

Chemical Forms of Zinc, Cadmium, and Lead in Surface Water

Metal Examined

Concentration [g-dm–3] Ionic Labile Stable Forms Complexes Complexes

Zinc Cadmium Lead

45.2 0.038 6.29

6.0 0.048 3.61

Source: Szpakowska and Karlik 1996.

104.2 0.048 4.95

Ionic Forms

% of Form Labile Complexes

Remain (stable)

29.1 28.4 42.3

3.8 35.8 24.3

67.1 35.8 33.4

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proportion of ionic forms was found in ground water (from 0.9 to 25.2%), while in surface water the amount of metal in this form ranged from 28.4 to 42.3%. Labile forms of metal occurred in greater quantities in ground water (24.1 to 57.8%), significantly due to a very high percentage of Pb (57.8%) and relatively high proportions of Zn (24.1%) in these forms. The forms of heavy metal bonds with organic compounds and their concentrations in waters can be affected not only by chemical composition of dissolved organic matter but also by quantity of dissolved organic matter (Karlik et al. 1996, Karlik and Szpakowska 1999). The surface and ground waters studied had a high concentration of organic matter. Therefore, a high proportion of metals in the form of stable complexes was found there. The stable forms (permanent complexes and strong chelates) were higher in ground water than in surface water (Tables 7.6 and 7.7) (Szpakowska and Karlik 1996). Such high concentrations of metals in the form of stable complexes in ground waters resulted from the higher concentration of humic acids in these waters (Figure 7.6). Humic acids are known to possess strong chelating properties and are able to form stable bonds that were destroyed after UV radiation. Estimation of metal form is very important for forecasting toxicity and transport of metals in the aquatic environment. For the study of the detoxification of waters it is not enough to determine the metal form bound to organic compounds; it is also necessary to estimate the stability of such binding. According to Tubbing et al. (1994), labile complexes, for example copper, with natural ligands such as humic acids can also be toxic to algae.

ASSOCIATION OF METAL IONS WITH HUMIC SUBSTANCES IN NATURAL WATER The solubility of several metals in water is much greater than expected from calculations based on the inorganic ions of the medium. For example, about 90% of soluble iron is bound to HS, and its solubility is greater than one can conclude from solubility constants (Weber 1988). Because this increase in solubility was related to complexation, adsorption, or reduction by HS, the study tends to estimate the proportion of heavy metals in a form bound to HS. In ground waters the amounts of bound lead and copper were higher than in surface water (in the case of Pb by 84.5% and by 49.9% for Cu) (Table 7.8). In the case of Cd, strong complexing ability was found for humus isolated from ground water under field, whereas five

Table 7.8

Binding Ability toward Heavy Metals of 1 g Humic Substances Isolated from Waters of Area A [g·g–1]

Type of Water Ground water under field Ground water under meadow Surface water of mid-field pond

Cadmium

Copper

Lead

0.528 0.113 0.117

27.6 27.0 13.7

46.4 45.6 7.1

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times lower binding of Cd was observed for HS obtained from ground water under meadow and surface water of mid-field pond. In estimating the amount of heavy metals bound to 1 g of HS, similar complexing abilities of HS isolated from ground water under meadow and field toward copper and lead were found. A smaller amount of copper in a form bound to HS in surface water may result from uptake of this metal by plants. Copper is easily taken by plants, in both ionic form and in complexes (Ozimek 1988). Research indicated that 1 g of HS isolated from ground water had stronger chelating properties toward heavy metals than HS obtained from surface waters. This finding may be connected with the different structure of HS in these waters, for example, higher proportion of humic acids in HS from ground water. HS have a reduction potential range of about 0.5 to 0.7 volts (vs. the standard hydrogen electrode) and are unlikely to affect oxidation. Undoubtedly there is a synergic process in which extremely low concentrations of metal ions are strongly complexed by humic acid, thus shifting the equilibrium toward the complexed metal ion. The total binding of HS for metal ions is 200 to 600 µmol·g–1. Approximately one third of this total is cation exchange sites and the remainder is complexing sites (Weber 1988). Complexations of metals by HS carboxylic and phenolic groups is very important for water migration of heavy metals, influencing their concentrations in water as well as in sediment. Bonds of high molecular organic substances with metals were determined on a sample of copper, which is often chosen for analyses. Using the method of sorption on Amberlite XAD-2 enabling separation of organic substances into polysaccharides, polypeptides, and humic substances, the degree of their binding with copper was determined (Table 7.9). Copper in ionic form constitutes 39.1% of its total concentration and in colloidal form 24.8%. The bound copper (with HS and PP) contribution was 32% of total concentration. A study by Linnik and Nabivanets (1984) showed that proteinpolypeptides fraction released by macrophytes can bind large amounts of copper forming metal-organic complexes. As was indicated in other studies (Thurman 1985, Szpakowska 1999), organic substances contain acidic functional groups, of which about one half are carboxylic acids, which are primarily responsible for binding metals and forming complexes (Shuman et al. 1990). Weber (1988) suggests that complex stability is highest for copper, intermediate for lead, and weakest for cadmium. Higher complex stability explains higher affinity of copper than cadmium and the displacement of the latter from complexes (Tubbing et al. 1994). Table 7.9

Chemical Forms of Copper Occurrence in Surface Water

Metal Forms Ionic Bound to polysaccharides and polypeptides Bound to humic substances Colloidal

Concentration [g·dm–3]

% of Total Concentration

11.15 4.80 4.35 7.07

39.1 16.8 15.2 24.8

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Table 7.10

179

Mean Concentration of Different Forms of Heavy Metals

Water Examined

Ground Water Under Field Under Meadow g·dm–3 % g·dm–3 %

Surface Water of Mid-Field Pond g·dm–3 %

Cd

Inorganic Organic Total Range

0.300 0.006 0.306 (0.2–0.3)

98 2 100

0.300 0.019 0.319 (0.1–0.4)

94 6 100

0.23 0.25 0.48 (0.2–1.3)

48 52 100

Pb

Inorganic Organic Total Range

1.76 0.83 2.59 (1.6–5.0)

68 32 100

2.15 0.78 2.93 (1.3–0.4)

73 27 100

1.42 1.42 2.84 (1.6–5.1)

50 50 100

Cu

Inorganic Organic Total Range

3.02 1.68 4.72 (2.4–14.2)

64 36 100

2.50 2.05 4.56 (1.8–13.6)

55 45 100

2.26 4.58 6.84 (2.8–27.2)

33 67 100

Zn

Inorganic Organic Total Range

7.16 0.56 7.52 (5.9–11.5)

93 7 100

7.12 0.94 8.06 (3.8–24.6)

88 12 100

9.68 6.43 16.11 (5.4–35.8)

60 40 100

·

Source: Zyczyn´ ska-Ba l oniak et al. 1993.

THE EFFECT OF MEADOW BELT ON HEAVY METAL SPECIATION The study carried out in the Wielkopolska region indicated that heavy metals migrating with ground water from the field under the meadow to the pond undergo speciation. The cation forms are bound by DOM to metal-organic complexes. For example, 50% of cadmium, a very toxic element, is transformed from the inorganic ionic form to organic form during its movement to the pond (Table 7.10). The concentration of inorganic copper passing from the field and meadow into the pond drops, while the organic form rises by 30%. Similar changes occur in the other cations. In the mid-field pond, the concentrations of lead and zinc in the organically bound form increase significantly. These observations confirm that the ecosystem character not only considerably affects the composition of DOM in waters, but also changes the form of heavy metals (speciation) carried away from the fields. Analysis of metal complexation competition for binding sites ought to be considered. For example, divalent ions, such as calcium, would compete for the copper binding site. The binding strength for calcium would be 100 to 1000 times less, but the concentration of calcium in ground waters is typically high (Mantoura 1981). Thus, the calcium would probably occupy most of the binding sites for copper. In waters examined in our study, concentrations of calcium were very high and amounted to 237.4 mg·dm–3.

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CONCLUSION The literature on soil organic substances is immense, but the organic matter of waters has received far less attention. The studies carried out in the Turew landscape indicated high concentrations of dissolved organic substances in waters situated in the agricultural areas. Land-use practices are a significant factor affecting the increase in the transport of organic matter. The water migration of DOM from agroecosystems and the methods of limiting it constitute the basic problem in the protection of aquatic environment. From the study presented, one can conclude that biogeochemical barriers, such as meadow belts, are very effective in limiting free DOM migration. Organic matter in water has great ecological and geochemical significance. On the one hand, DOM is an important energy source for microbially based aquatic food webs but is also very essential to the interaction of DOM with such elements as the heavy metals. Particularly important in this phenomenon are humic substances, which can bind large amounts of zinc, cadmium, lead, and copper. In the case of cadmium, strong complexing ability was found for humus isolated from ground water under fields, whereas five times less binding of cadmium was observed for HS isolated from surface water. There are two main reasons for studying the interactions of organic material with metal ions: to understand its chemical nature and to understand its effects on the environment. Such studies are very important for prediction of the reactivity, toxicity, and migration of metal ions in the aquatic environment where type of ecosystem plays a vital role. In particular, humic acids are very active in life cycles of flora and microorganisms. There is no doubt that these substances compete with definite organic compounds of known structure (e.g., polysaccharides), which are much more effective in their specific reactions. On the other hand, the latter compounds take part in only specific reactions while humic acids have an immense spectrum of effects on biota. Identification of all organic compounds is not possible at present, but the description of properties (e.g., binding ability of metals) may help in differentiating organic matter from different sources.

REFERENCES Ch l opecka A. and Dudka S. 1991. Wp l yw osadów s´ ciekowych na zawartos´ c´ metali s´ ladowych w glebie i ros´ linach oraz na wymywanie tych pierwiastków z gleby. Zeszyty Naukowe AGH, Sozologia i Sozotechnika 31: 79–85. Easthouse K. B., Mulder J., Christophersen N., Seip H. M. 1992. Dissolved organic carbon fractions in soil and stream water during variable hydrological conditions at Birkenes, Southern Norway. Water Resources Res., 28 (6): 1585–1596. Gaffney J. S., Marley N. A., Clark S. B. 1996. Humic and fulvic acids. Isolation, structure and environmental role. American Chemical Society, Washington, D.C. Golimowski J., Sikorska A.1983. A voltammetric method of the determination of toxic heavy metals in surface waters. Chemia Analityczna 28: 411–420. Górniak A. 1996. Substancje humusowe i ich rola w funkcjonowaniu ekosystemów s l odkowodnych. Praca habilitacyjna. Uniwersytet Warszawski, Filia w Bia l ymstoku: 151 pp.

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Gron C., Torslov J., Albrechtsen H. J. 1992. Biodegradability of dissolved organic carbon in ground water from an unconfined aquifer. The Science of the Total Environment 117/118: 241–251. Hessen D. O., Tranvik L. J. 1998. Aquatic humic substances. Ecological Studies 133, SpringerVerlag, Berlin: 178–195. Jansson M. 1998. Nutrient limitation and bacteria-phytoplankton interactions in humic lakes. In Aquatic Humic Substances. D. O. Hessen, L. J. Tranvik (Eds.), Ecological Studies 133, Springer-Verlag, Berlin: 178–195. Karlik B., Szpakowska B., Otabbong E., Siman G. 1996. Migration of mineral elements bound to dissolved organic compounds in agricultural watershed. Pol. Ecol. Stud. 22, 3–4: 95–103. Karlik B., Szpakowska B. 1997. Dissolved organic matter and chemical forms of heavy metal in waters of agricultural basin. Roczniki Akademii Rolniczej w Poznan´ iu, 194: 39–46. Karlik B., Szpakowska B. 1999. Effect of dissolved organic matter on metal speciation in waters from agricultural area. In Paysages agraires et Environnement. S. Wicherek (Eds.). CNRS, Paris: 253–259. Karlik B., Szpakowska B. 2001. Labile organic matter and heavy metals in waters of agricultural landscape. Pol. J. Environ. Stud. 10 (2): 85–88. Kramer J. R., Brassard P., Collins P., Clair T. A., Takats P. 1990. Variability of organic acids in watersheds. In Organic Acids Aquatic Ecosystems. E. M. Perdue, E. T. Gjessing (Eds.). John Wiley & Sons, New York: 127–139. Kundzewicz Z., Szpakowska B., Sibrecht R. 1994. Modelling of chemicals dissolved in waters in agricultural landscape. In Hydrochemistry: Hydrological, Chemical and Biological Processes of Transformation and Transport of Contaminants in Aquatic Environments. Proceedings of the Rostov-on Don Symposium 219: 231–239. Linnik T. N., Nabivanets B. J. 1984. The state of metal ions in natural waters. Acta Hydrochim. Hydrobiol. 12: 335–361. Lush D. L., Hynes H. B. N. 1978. Particulate and dissolved organic matter in a small partly forested Ontario stream. Hydrobiologia 60: 177–185. Maier W. J., Gast R. G., Anderson C. T., Nelson W. W. 1976. Carbon contents of surface and under ground waters in south-central Minnesota. J. Environ. Qual. 5 (2): 124–128. Malcolm R. L. 1985. Geochemistry of stream fulvic and humic substances. In Humic Substances in Soil, Sediment and Water. G. R. Aiken, D. M. McKnight, R. L. Wershaw, P. MacCarthy (Eds.). John Wiley & Sons, New York: 181–209. Mantoura R. F. C. 1981. Organo-metallic interactions in natural waters. In Marine Organic Chemistry. E. Duursma, R. Dafson (Eds.). Elsevier, Amsterdam: 179–224. Mart L., Nürnberg H. W., Valenta P., Stoeppler M. 1978. Determination of levels of toxic metals dissolved in sea water and inland waters by different pulse anodic stripping voltammetry. Thalassia Jugoslavica, 14 (1/2): 171–188. Meili M. 1992. Sources, concentrations and characteristics of organic matter in softwater lakes and streams of the Swedish forest region. In Dissolved Organic Matter in Lacustrine Ecosystems: Energy Source and System Regulator. K. Salonen, T. Kairesalo, R. I. Jones (Eds.). Kluwer Academic Publishers, Dordrecht: 23–41. Meyer J. L. 1990. Production and utilization of dissolved organic carbon in riverine ecosystems. In Organic Acids in Aquatic Ecosystems. E. M. Perdue, E. T. Gjessing (Eds.). John Wiley & Sons: 281–299. Misztal M., Smal H., Lige˛ za S. 1997. Sk l ad chemiczny i sk l ad grupowy rozpuszczonej substancji organicznej wód jeziora Piaseczno i p l ytkich wód gruntowych zlewni w s´ wietle badan´ z lat 1992–1996. In 18 Zjazd Hydrobiologów Polskich: 51.

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Tubbing D. M. J., Admiraal W., Cleven R. F. M. J., Igbal M., Van de Meent D., Verweij W. 1994. The contribution of complexed copper to the metabolic inhibition of algae and bacteria in synthetic media and river water. Water Res. 28 (1): 37–44. Weber J. H. 1988. Binding and transport of metals by humic materials. In Humic Substances and Their Role in the Environment. F. H. Frimmel, R.F. Christman (Eds.). John Wiley & Sons, New York: 165–178. · Zyczyn´ ska-Ba l oniak I., Szpakowska B. 1989. Organic compounds dissolved in water bodies situated in an agricultural landscape and their role for matter migration. Arch. Hydrobiol. Ergebn. Limnol. 33: 315–322. · Zyczyn´ ska-Ba l oniak I., Szpakowska B., Ryszkowski L., Pempkowiak J. 1993. Role of meadow strips for migration of dissolved organic compounds and heavy metals with ground water. Hydrobiologia 251: 249–256.

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CHAPTER

8

Influence of Landscape Mosaic Structure on Diversity of Wild Plant and Animal Communities in Agricultural Landscapes of Poland Lech Ryszkowski, Jerzy Karg, Krzysztof Kujawa, Hanna Go l dyn, and Ewa Arczyn´ ska-Chudy

CONTENTS Introduction............................................................................................................185 Impoverishment of Plant Communities Resulting from Agriculture ...................187 Plant Species Richness in the Agricultural Landscape.........................................190 Influence of Agriculture on Animals.....................................................................194 Abundance and Diversity of Animal Communities in an Agricultural Landscape...............................................................................199 Prospects for the Biological Diversity Management in Agricultural Landscapes ..................................................................................209 References..............................................................................................................211

INTRODUCTION According to prevailing opinion, agricultural activity eliminates many wild plant and animal species and is among those human actions that impoverish living resources. Attempts to eradicate any plant competitors and the pests and pathogens to cultivars result in enormous simplification of biotic communities in cultivated fields. Each year many new chemicals are used to control organisms menacing crops. In order to obtain predictive and increasingly higher yields, farmers control soil

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185

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moisture and its pH, irrigate fields, introduce fertilizers, level earth surface, and shape fields. All those efforts, together with frequent tillage and other kinds of farmer interference in agroecosystem structures and processes, change the living conditions of many wild organisms and often lead to their disappearance. Intensification of agriculture also leads to alteration of countryside structure. Simplification of crop rotation patterns due to increasing specialization of plant production and formation of large fields to facilitate mechanization of work are frequently observed. Eradication of patches of mid-field forests, shelterbelts (rows of mid-field trees), hedges, field margins, stretches of meadows, and riparian vegetation strips is performed on a large scale during field consolidation. Drainage of mid-field small wetlands or small ponds also leads to the simplification of the agricultural landscape structure. All these activities eliminate refuge sites for many organisms in the agricultural landscape. One can conclude, therefore, that the interests of agriculture and nature conservancy are contradictory, and this conclusion was frequently used and broadly disseminated in general as well as in specific discussions on nature protection problems. The problem of protecting living resources became the central theme not only among biologists but also in political and administration circles when evidence was presented that the world’s flora and fauna are disappearing at an alarming rate (e.g., Wilson and Peter 1988, Reaka-Kudla et al. 1997, Vitousek et al. 1997). These concerns culminated in the Biodiversity Convention during the World Summit in 1992. Following the Biodiversity Convention, several policies were recommended by the Council of Europe as well as by the European Commission, such as the PanEuropean biological and landscape diversity strategy, the European Ecological Network, and Nature 2000. All these policies stress integrating nature protection with sectoral activities, indicating a substantial change from the previous point of view that nature should be shielded against human activity in order to ensure its successful protection. That change, still opposed by many biologists, was stimulated by a slowly growing consensus that the way in which resources have been used, rather than the fact that they are used at all, has caused the threats to nature. The possibility that agriculture could be integrated with biodiversity protection is related to changing cultivation technologies (Srivastava et al. 1996) and to managing agricultural landscape structures to provide survival sites for biota (Baldock et al. 1993, Ryszkowski 1994, 2000). There is no doubt that high-input modern farming practices frequently pollute water and soil, compact soil, and stimulate erosion. But inappropriate agricultural practices can be modified to mitigate their adverse effects on the biota and environment. Diversification of the agricultural landscape pattern through introduction of refuge sites can mitigate biota impoverishment due to intensive farming, at least with respect to some plant and animal communities. To evaluate that prospect of biodiversity protection, the results of the long-term studies carried out in the Research Centre for Agricultural and Forest Environment in Poznan´ , Poland, as well as other Polish investigations, are presented.

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IMPOVERISHMENT OF PLANT COMMUNITIES RESULTING FROM AGRICULTURE According to the Main Statistical Office more than 60% of Poland crop production is based on cereals (wheat, rye, barley, oats, maize, and triticale, which is the product of wheat and rye hybridization used for fodder). The production of potatoes, sugar beets, rape seed and common agrimony, leguminous crops for human consumption and fodder (peas, beans, clover, alfalfa), and other crops constitute the rest of plant production. In 1998 cereals comprised 70.7% of arable land, cultivated on 31.9% of the total territory of Poland. The total land area used to cultivate cereals is greater than the total forest area, comprising a total of 28.2% of the entire country. The arable land in Poland is dominated by light soils, and, when cereals are cultivated too frequently on the same field, depleted nutrients and decreased soil organic matter can result if pulse crops are not included in the crop rotation pattern or if organic fertilizers are not applied. Thus, overall simplification of the plant cover structure in Poland because of agricultural activity resulted in the dominance of cereals. The simplification of plant cover structure is even more advanced because wheat and rye cultivations cover 55.5% of the total area under cereals, and during 1988–1998 the contribution of area under wheat increased by 20.7% while the area under cultivation of rye, barley, and oats decreased. Wheat fields constitute, therefore, not only the dominant element of the countryside, but they also influence distribution of many organisms in the agricultural landscape and influence their prospects for migration and survival. Growing alongside cultivated plants are weeds, which are inevitable components of agroecosystems but controlled to a large extent by farmers. During their long coexistence with cultivars under a regular sequence of tillage activities, weeds adapted to survive and thrive in agroecosystems. Their potential to adapt to cultivation measures is great, and despite the use of highly effective herbicides the diversity and even density of weeds has increased recently (Ghersa and Roush 1993, Cousens and Mortimer 1995). Chemical control limitations led to the development of integrated weed management (IWM), which combines chemical control tactics with mechanical and biological measures. The goal of IWM is to use such control measures to reduce and prevent weed community adaptation to field management (Fick and Power 1992, Swanton and Murphy 1996, Johnson et al. 1998). Herbicides, crop rotation, and tillage practices are considered the most important elements of weed control programs in the literature. The ranking of those factors varies according to different studies, especially when development of resistance to herbicides was discovered; nevertheless, it is believed that the IWM practices relying on several control methods can control weed populations below the economical threshold of harmful effects on yields (Huffaker et al. 1978, Fick and Power 1992, Christoffoleti et al. 1994, Cousens and Mortimer 1995, Buhler et al. 1995, Barberi et al. 1995, 1997, Exner et al. 1996). The general consensus seems to be that it is not possible to eradicate weed communities, but the IWM methods could help to maintain noneconomical densities of their populations.

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In Poland, about 400 species of weeds were detected in various communities characteristic for main cultivars (Adamiak and Zawis´ lak 1990). During the last decades, the impoverishment of weed communities was observed in Poland by many scientists (Borowiec et al. 1992, Korniak 1992, Fija l kowski et al. 1992, Sendek 1992, Trzcin´ ska-Tacik 1992, Warcholin´ ska 1992, Stupnicka-Rodzynkiewicz et al. 1992a, 1992b). Greater impoverishment of weed communities is observed in regions with more intensive agriculture. The following factors are considered to limit abundance and diversity of weed communities: • Use of herbicides — Eliminated are stenotic species well adapted to specific cultivars which are substituted by ubiquitous species communities mainly composed by monocotyledonous species or dicotyledonous ones resistant to herbicides (Borowiec et al. 1992, Gould 1991, Warwick 1991, Korniak 1992a, Trzcin´ skaTacik 1992, Warcholin´ ska 1992, Fija l kowski et al. 1992, Stupnicka-Rodzynkiewicz et al. 1992a, 1992b). • Type and amounts of fertilizers — Increasing inputs of fertilizers eliminates oligothrophic species. Applications of higher amounts of mineral nitrogen or farm manure bring about expansion of nitrogenous species (Adamiak and Zawis´ lak 1990a, Korniak 1992a, Warcholin´ ska 1992). • Simplification of the crop rotation pattern — When crop rotation is simplified, weed communities likewise become less diverse; a simplified and stable community develops, composed of a few abundant species. Observed dominance of cereals in crop rotation pattern leads to simplified weed communities composed mainly of such abundant species such as Apera spica-venti, Centaurea cyanus, Galium aparine, Matricaria perforata, Avena fatua, and Echinochloa crus-galli. • Clearing cultivar seeds from weed’s diaspores in winnowing machines — This clearing limits the dispersion of adopted species to dissemination together with the cultivated plant. Thus, for example, due to the winnowing process such species as Bromus arvensis, B. secalinus, and Agrosemma githago are disappearing from weed communities (Warcholin´ ska 1992). • Abandonment of cultivars — Abandoning cultivars results in disappearance of weed communities associated with that cultivation. Thus, for example, evanescence of the weed community associated with common flax (Linum usitatissimum) cultivation observed recently is the direct effect of abandoning that cultivar.

Diversification of plant cover structure in landscape influences the richness of weed communities. Agricultural landscapes with less intensive tillage practices and field-mosaics intersected by many uncultivated refuges, such as field margins, stretches of meadows, small afforestations, and wetlands, have a higher diversity of weed communities (more than 300 weed species) than do areas with more intensive cultivation (less than 200 species of weeds) (Figure 8.1). In the Turew agricultural landscape (an area studied for 30 years by scientists from the Research Centre for Agricultural and Forest Environment; see area description in Ryszkowski et al. 1996), 193 species associated with cultivations were found. In this community of plants growing in cultivated fields, 57% of the species are native and associated with nonproductive habitats surrounding the fields. In addition, in the cultivated fields, 28%

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176

361 263

277 179

War s z aw a

o 193

320 258 374

348

219 371

Figure 8.1

Number of weed species in agricultural landscapes with low and high regime of mineral fertilization (Go l dyn Arczyn´ ska-Chudy unpublished data, Ho l dyn´ ski 1991, Kutyna 1988, Latowski et al. 1979, Labza 1994, Skrzyczyn´ ska 1998, Skrzyczyn´ ska and Skrajna 199, Szotkowski 1973, Warcholinska 1976, 1983, 1997, Wika 1986).

of the species are archaeophytes, plants that invaded Poland before the 15th century, and have been associated with cultivations for a very long time. The newcomers (kenophytes) that became naturalized during the last few centuries make up 7% of the total weed community. All species, in addition to cultivars, found in cultivated fields also exist in surrounding nonproductive habitats, from where they invade fields. Thus, the influence of the plant community living in the total landscape on species composition in cultivated fields is substantial. Similar results were found by other scientists (Skrzyczyn´ ska 1998, Warcholin´ ska and Pote˛ bska 1998, Skrzyczyn´ ska and Skrajna 1999, Warcholin´ ska and Mazur 1999). The dispersion of plants from untilled elements of the landscape into cultivated fields is the reason why intensification of herbicide application does not totally eliminate weeds but only suppresses their abundance.

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Among the plants growing in cultivated fields of the Turew landscape one can find 18 species that are indicated in the “Red Data Books” of Polish flora (Warcholin´ ska 1986/1987). Communities of plants in cultivated fields can therefore constitute a reservoir of species that are vanishing throughout the entire country.

PLANT SPECIES RICHNESS IN THE AGRICULTURAL LANDSCAPE There is no doubt that intensification of agricultural production leads to the impoverishment of plant communities growing in cultivated fields. This trend consists of species loss as well as change in community species composition toward an increase of ubiquitous species resistant to herbicides as well as to other modern agricultural technologies. But the situation observed in cultivated fields does not indicate that the same trend is true for the entire landscape composed of mosaic habitats. The results presented below indicate that increased diversity of habitats within the landscape leads to a higher richness of plant species growing in the landscape. There is a surprisingly small number of studies on total flora in mosaic agricultural landscapes. The main attention of botanists has been directed to protected areas, such as national parks, or to more or less natural forest and grassland landscapes. In the Turew mosaic agricultural landscape, where cultivated fields make up 70% of the total area, 805 species of vascular plants have been detected to date (Go l dyn and Arczyn´ ska-Chudy 1998, Ryszkowski et al. 1998). A similar estimate of total number of species was reported by Borysiak et al. (1993) for the agricultural landscape of Szwajcaria Zerkowska, where cultivated fields cover little more than 70% of the total area. Analysis of species distribution shows that rich and diversified plant communities can be found in marginal habitats that function as refuge sites for the flora. In the Turew landscape, grasslands and an uncultivated, very old manor park harbor more than 300 species each (Table 8.1). The highest diversity of flora was Table 8.1 Number of Vascular Plant Species in Various Habitats of the Turew Agricultural Landscape Habitat Grasslands Shelterbelts and afforestations Manor park Roadsides Water reservoirs with rushes Cultivated fields Total landscape a

Total

Archaeophytes

Kenophytes

Diaphytesa

321 266 308 220 211 193 805

22 13 32 49 2 54 85

14 16 20 27 5 13 55

0 2 7 26 2 16 39

Diaphytes are newly introduced cultivated plants spreading to seminatural habitats or those that invade Poland now and are still not adapted to prevailing conditions. They are transported into Poland by cars, trains, and other means of transportation. Source: Updated from Ryszkowski et al. 1998.

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Table 8.2 The Number of Threatened and Protected Species of Vascular Plants in Various Habitats of the Turew Landscape Habitat Water reservoirs with rush Grasslands Afforestations and shelterbelts Manor place Roadsides Cultivated fields Total landscape

Threatened Species Poland Wielkopolska 3 6 — — — — 7

18 24 5 4 2 2 45

Protected Species Totally Partially 2 7 1 5 1 — 14

3 6 4 3 1 — 9

found in grasslands located mainly in the lower parts of the landscape close to small water reservoirs or along the drainage system of the landscape. In mowed grasslands, the common species prevail while in rush associations and in water reservoirs the threatened or protected species can also be found. The Turew landscape is located in the Wielkopolska region, where the intensity of agricultural production is greater than in most other areas of Poland. The higher anthropogenic pressure on nature leads to lower survival rates of the plants in the region compared to the entire territory of Poland. The International Union for Conservation of Nature and Natural Resources (IUCN) developed criteria for evaluation of species survival status. The term threatened used in Table 8.2 corresponds to the categories of endangered and vulnerable in IUCN standards. The list of threatened · species for the Wielkopolska region was published by Zukowski and Jackowiak (1995) and for the whole of Poland by Zarzycki et al. (1992). The status of vascular plant species found in the Turew landscape was determined with this information. A much higher number of threatened species was found according to the Wielkopolska Red Data Book than according to the Red Data Book for all of Poland, which shows that despite higher anthropogenic pressure, 45 threatened species survive well in the mosaic agricultural landscape of Turew. Water reservoirs and grasslands located in the agricultural landscape are the habitats that provide refuge sites for the greatest number of threatened species (Table 8.2). For example, in sedge communities, endangered and almost vanished species such as Carex davalliana, Gentiana pneumonanthe, Viola persicifolia, and Primula elatior were found. Those landscape elements are also overgrown by the plant communities most resistant to invasion by newcomer species (kenophytes and diaphytes). Among the 321 species constituting the grassland plant communities, only 14 newcomers to native flora succeeded in establishing themselves in those communities and none of the diaphytes that disseminate their propagules in the whole landscape succeeded (Table 8.1). A similar situation is observed in water plant communities. Only four species of newcomers are associated with the rich communities of native plants. Four types of water bodies occur in the Turew landscape: lakes, mid-field ponds, peat-holes, and ditches discharging water to drainage channels. If the water reservoir is not polluted by chemicals leached from the cultivated fields or by discarded wastes, then up to 100 species can be detected in reservoirs belonging to each category (Table 8.3). The majority of species harbored in each type of water body are common to all reservoirs studied.

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Table 8.3 Number of Vascular Plant Species in Water Reservoirs of the Turew Landscape Type of Water Body Lake Small ponds Peat-holes Drainage channels and ditches All water bodies

Number of Species

Species Restricted only to Examined Habitat

111 108 95 115 211

29 18 24 31 211

Undergrowth plants are important contributions to the shelterbelt list of plant species. Among trees, the two widely distributed species of newcomers are Robinia pseudoaccacia and Prunus serotina, which were introduced in the 19th century. In shelterbelts, especially old ones with Robinia, the high incidence of therophytes (21%) indicates increased human pressure (Ratyn´ ska and Szwed 1997). Under the conditions of intensive human management, the total number of kenophytes in shelterbelts is even higher than that found in cultivated fields (Table 8.1), which shows that newcomers easily settle in intensively managed afforestations. Nevertheless, the contribution of the native species is high, making up 88.0% of the total recorded in those habitats. Kenophytes make up 6% and the contribution of archaeophytes is 5%. In cultivated fields, 193 species were found. Weed communities were composed of common species, the majority of which are associated with cereal cultivations. Kenophytes make up 7% of the total weed species list, archaeophytes make up 28%, and diaphytes comprise 8%. Native species constitute 57% of the total number of species living in cultivated fields. Floristic analysis shows that out of 110 native species found in weed communities, 33 (30%) come from grasslands, 28 (25%) from water reservoirs, 24 (22%) from afforestations, and 10 (9%) from xerothermic swards that appear infrequently in the Turew landscape. Plants from all seminatural habitats found in the landscape have their input into weed communities, which indicates the importance of plant dissemination processes for building and maintaining weed diversity in cultivated fields. Very high plant diversity was found in stressed habitats, such as roadsides. Again, there was a high number of kenophytes species, amounting to 27 (11%), as well as a very high number of archaeophyte species, equal to 49 (19%) (Table 8.1). The highest number of diaphytes of all habitats was found in roadsides, amounting to 26 species (10% of total). The manor’s 20-ha park is characterized by a very high diversity of plants, surpassing the total diversity of plants found in the 2200 ha of shelterbelts and afforestations of the landscape studied. After evaluating the taxonomic status of various ecosystems in the studied agricultural landscape, one can state that seminatural grasslands and water plant communities harbor rich associations of native plants that show high resistance to invasion of alien species. Many species threatened by anthropogenic pressure also find refuge sites in such habitats. Higher anthropogenic pressure leads to greater opportunities for ubiquitous or alien species to flourish. That situation was observed not only in shelterbelts, roadsides, and cultivated fields, but also in mowed meadows and degraded water reservoirs.

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Table 8.4 The Species of the Most Abundant Families in the Turew Agricultural Landscape (TAL) and Wielkopolski National Park (WNP) Family

TAL %

WNP %

Asteraceae Poaceae Rosaceae Cyperaceae Fabaceae Caryophyllaceae Brassicaceae Scrophulariaceae Lamiaceae Polygonaceae Ranunculaceae Apiaceae

10.4 9.5 5.9 5.8 5.6 3.9 3.9 3.5 3.5 3.2 3.0 2.6

10.9 8.9 7.3 4.8 6.1 4.6 4.1 3.7 3.6 1.8 2.8 3.5

Contribution to total floristic list of species

60.8

62.1

In the mosaic agricultural landscape studied, 805 species of vascular plants were · detected, while Zukowski et al. (1995) estimated the number of species present in the nearby Wielkopolski National Park at 1120. Keeping in the mind that the National Park has more types of habitat than does the landscape studied, it is nonetheless clear that the mosaic Turew landscape is characterized by a rich plant community. Studying the higher taxonomic categories, one can find 494 genera and 116 families of plants in the Wielkopolski National Park, while in the mosaic Turew landscape 350 genera and 101 families were detected. The similarity of the list of Turew landscape flora to the list of plants in the National Park is underscored by the fact that the 12 families richest in species (with 60% of the total recorded species in each area) are the same in both locations (Table 8.4). The order of family importance, estimated by the percentage of the total for each species, is almost the same in both locations. Thus, the mosaic agricultural landscape reflects well the potential for species diversity in the region. In comparison to other studies on landscape species diversity, it can be stated that the lack of large forest complexes plus intensive human interference very drastically decreased the number of species in Turew afforestations and shelterbelts. · Thus, in the forest complexes of Wielkopolska Park, Zukowski et al. (1995) estimated 508 species, and 581 species were found in forest complexes of KrakówWielun´ Upland (Wika, 1986) while in Turew’s afforestations only 266 species can be found. Native species comprise 75% of the species list of the Wielkopolski National Park and almost the same amount (77%) in the Turew mosaic agricultural landscape. The taxonomic richness of the mosaic agricultural landscape can also be shown by the following comparison with national parks of an area similar to that studied in Turew. In Bia l owiez· a, 725 vascular plant species were detected. According to estimates, the following numbers of species can be found: Drawien´ ski — 1000; Magurski — 400; Wigierski — 1300; and Wolin´ ski — 1300 (Cyrul 2000, G l owacin´ ski 1998). Although

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these estimates are not exact, they indicate, nevertheless, the high diversity of plant communities in the agricultural landscape studied in Turew. These comparisons of the number of plant species do not indicate the qualitative differences between mosaic agricultural landscapes and natural parks. In the Wielkopolski National Park, botanists found 51 protected species (38 totally protected and 13 partially). According to the Wielkopolska Red Data Book, the number of threatened species was 184 and according to the threatened species list of Poland, there were 26 species threatened. These estimates are higher than those obtained in the Turew agricultural landscape but not as high as one could presume, relying on the prevailing opinion that agriculture exerts widespread negative impacts on nature protection. Diversification of the agricultural landscape structure amends, to some extent, the negative effects of agricultural activities on the plant diversity.

INFLUENCE OF AGRICULTURE ON ANIMALS To increase production, farmers subsidize energy to simplify the plant cover structure both within cultivated fields (selection of cultivars well adopted to a narrow set of environmental conditions which increase production under controlled growth conditions and also eliminate weeds) and within the agricultural landscape (eradication of small afforestations, shelterbelts, mid-field ponds, wetlands, and others). Use of fertilizers and pesticides, ploughing of soils, and drainage of fields as well as application of other modern agriculture technologies affect the survival rates of animals living in cultivated fields, often leading to impoverishment of animal communities. There are many publications on the impact of various agricultural technologies on particular groups of animals, but there is a scarcity of studies concerning reactions of the total set of animals living in agroecosystems. A few compilations of estimates soil fauna data from different periods or places were performed by Russel (1977), Hendrix et al. (1986), Hansson et al. (1990), Prasad and Gaur (1994). The long-term studies on ecology of agricultural landscapes, carried out by the Research Centre for Agricultural and Forest Environment in Turew (Ryszkowski et al. 1996), included complex investigations on total above- and belowground animal communities and aimed at evaluation of their functional reactions to agricultural activity (Karg and Ryszkowski 1996). Animals, as compared to vascular plants and microorganisms, comprise a small part of total organic matter, amounting to less than 1% of the total. Total organic mass during the plant growing season was almost 3 times higher in the meadow than in the wheat field studied in the Turew landscape but the differences in animal biomass amounted to 4.4 times in favor of the meadow (Table 8.5). Thus, in cultivated fields not only is a decline of animal biomass observed, but the rate of animal community suppression is greater than in the entire organic system. The two ecosystems compared were located side by side. If one considers a meadow as an example of an ecosystem with less intense farmer interferences (no ploughing, no change of growing plants after harvest, a high diversity of plants, among others characteristics) than a wheat field, one can then infer that the whole

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Table 8.5 Distribution of Biomass (mg d.w.·m–2) in Components of a Wheat Field and a Meadow Ecosystem (to 30 cm soil depth) Wheat

Meadow

Above ground (total) Plants Animals

265014 264660 354

158647 158400 247

Below ground (total) Plants (roots) Animals Bacteria Fungi Litter

830979 104580 2109 172000 516000 36290

2915167 937500 10637 460000 1380000 127030

1095993

3073814

Total

Source: Modified from Ryszkowski et al. 1989.

Table 8.6 Season-Long Mean Biomass (mg d.w.·m–2) of Soil Invertebrates in Soil under Continuous Rye and Rye in 4-Year Rotation Pattern Site of Study Kind of cultivation

Mean values of biomass (Protozoa, Nematoda, Annelida, Acarina Insecta)

Wielichowo (1983–1984)

Jelcz-Laskowice (1986–1989)

Rye at 13th year of continuous cropping

Rye in 4-year rotationa

Rye at 12th till 15th year of continuous cropping

Rye in 4-year rotationa

1108.6

1327.2

2265.6

6502.0

a

Mean values of rye after potatoes, and rye after pea in Norfolk rotation. Source: Calculated from data of Karg et al. 1990.

animal community is impoverished by agricultural activity. This conclusion can be supported by studies on the effects on soil biota of continuous cropping of rye, which can be considered a more intensive system than crop rotation (Ryszkowski et al. 1998). Simplification of plant cover to continuous cultivations of rye resulted in further intensified impoverishment of total soil animals (Table 8.6). More striking than changes in biomass due to cultivation are changes in functions of the soil biota. Smaller body sizes were detected in many groups of edaphon (soil animals) when the body weight distribution of animals living in the cultivated fields was compared with those populating the meadow (Table 8.7). With the exception of Lumbricidae, all groups living in the meadow were characterized by the higher contribution of species having heavier bodies. The contrasting result found in Lumbricidae is due to observation that young specimens made a higher contribution to earthworm populations living in the meadow soil, which means that cultivated fields were populated by only adult specimens. Differences in mean body weights were

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Table 8.7 Mean Individual Body Weight (mg live weight) Distribution of Edaphon in Wheat Field and Meadow

Taxon Wheat field Meadow

Winged Insect Larvae

Collembola

Lumbricidae

Enchytraeidae

Acarina

Nematoda

5.75 42.75

0.0052 0.0055

506.0 317.0

0.161 0.192

0.0104 0.0107

0.000637 0.000788

Source: Ryszkowski 1985.

especially distinct in winged insect larvae; in the meadow soil they were 7.4 times heavier in mean body weight than larvae found in the wheat field soil. Thus, it can be inferred that agricultural activity of farmers creates conditions that can be tolerated by smaller animals, and by that token agriculture favors r-strategy species, in the terminology of MacArthur and Wilson (1967) — species having high reproduction rates and characterized by small body sizes survive in field soil although they are exposed to high mortality rates. Because of the well-known inverse relationship between body weight and metabolic rate, smaller animals use higher amounts of energy per mass unit to maintain their activity than do larger ones. According to estimates of energetic costs to maintain the total set of animals in the studied wheat and meadow ecosystems, the animals in meadow expended 0.23 kJ·mg–1 ·m–2 during 225 days of the plant growing season, while in the wheat field they expended 0.75 kJ·mg–1 ·m–2 (Ryszkowski and Karg 1996). Thus, due to the changes in body sizes of individual species, maintenance of the standing biomass of the entire wheat field community requires more intensive dissipation of energy than in the meadow community. Further simplification of plant cover to continuous cropping of rye can increase the energetic expenses for maintenance of the biomass unit in the plant growth season from 0.82 kJ·mg–1 ·dw·m–2 in animal communities living in soil under rye grown in rotation to 0.93 kJ·mg–1dw·m–2 in rye cultivated in continuous cropping in Wielichowo studies.* The studies carried out in Jelcz-Laskowice showed much greater differences. In this last situation, maintenance costs of unit biomass of edaphon during the vegetation season in rye grown in rotation was equal to 0.38 kJ·mg–1dw·m–2, and in continuous cropping this cost increased to 0.79 kJ·mg–1dw·m–2. In all of the above energy estimates of maintenance costs of total communities, the metabolism rates were calculated by measuring specific live body weights for the studied taxonomic groups and using specific equations relating body weights and respiration rates for each taxonomic group, including corrections for changes in temperature (Ryszkowski and Karg 1996). In order to make all biomass estimates comparable, the dry weight was used for calculations of efficiency index of energy use for biomass maintenance. Estimates of total community dissipation of energy per unit of biomass (index of efficiency) were calculated by estimating the energy maintenance costs of the total community (the sum of maintenance costs of particular groups), then * The studies on ecological effects of continuous cropping were carried out in two experimental farms: Wielichowo and Jelcz-Laskowice. The detailed description of the soil characteristics and tillage methods, as well as methods of studies, are provided by Ryszkowski et al. 1998a.

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Table 8.8 Mean Studied Biomass (mg dw·m–2) and Energy Costs Maintenance (kJm–2) of Soil Invertebrates during the Growing Season

Taxon Protozoa Nematoda Lumbricidae Enchytraeidae Acarina Collembola Winged insects mainly larvae Total

Wheat Field Energy Biomass Maintenance

Meadow Energy Biomass Maintenance

440.0 557.4 940.0 50.9 11.2 47.4 109.6

1190.0 314.6 56.0 26.5 1.3 20.5 14.6

525.0 816.6 3840.0 198.6 475.7 65.6 4883.0

1360.0 499.5 254.2 88.7 22.6 21.1 223.7

2156.5

1623.5

10,704.5

2469.8

Source: Modified from Ryszkowski and Karg 1996.

dividing that value by the sum of dry weights of populations composing community (Ryszkowski and Karg 1996). In all the ecosystems studied, Protozoa made the greatest contribution to energy flow through animals. Second in the rank, but much lower than Protozoa, is the contribution of Nematoda to dissipation of energy. The soil larvae of insects with very low contributions to energy flow through total soil community consisted of the group of large invertebrates that react very strongly to the intensity of farmer interference with ecosystems. Greater intensity of agricultural interference has resulted in elimination of large insects. The mean body size of winged insect larvae in meadow was about 7.4 times heavier than the mean body weight of larvae found in the wheat field (Table 8.7). Insect larvae in meadow made up 45.6% of the total community biomass, but contributed a total of only 9.0%. In wheat cultivation their contribution to biomass structure was 5.0%, but in terms of dissipated energy their share was 0.8% (Table 8.8). The same was true for earthworms. In terms of biomass, their contribution was substantial, while they dissipated only a small amount of energy. All these comparisons show that agricultural activity impoverishes animal communities. More simplified plant cover structure accompanied by frequent farmer interference with soil conditions relates to more intensive energy flow through edaphon communities. This observation means that the use of organic matter by animal communities is more intensive in cultivated fields than in other ecosystems of the agricultural landscape and that energy storing capacities are diminished by elimination of large and long-lived species. Turnover of the organic matter in agroecosystems is therefore increased. Among other functional changes appearing under agricultural pressure, Karg and Ryszkowski (1996) and Ryszkowski and Karg (1996) found that belowground fauna (including hedgehog population) constituted 86% of the total biomass of animals living in the wheat field, while, in the meadow, biomass of edaphon constituted 98% of the total community. The higher share of aboveground fauna in the cultivated field could mean that animal migration processes between ecosystems in a landscape can compensate to some extent the biota impoverishment caused by tillage. This

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factor is discussed later in this chapter when influence of landscape structure on insect and bird communities is shown. Another functional characteristic of agroecosystems is that herbivores constitute a higher proportion of trophic structure in the wheat field than in the meadow (Ryszkowski and Karg 1996). The same situation is observed in many other crops. For example, in potato cultivation, Colorado beetles (Leptinotarsa decemlineata), a pest to this cultivar, constitute 84% of the total biomass of the aboveground insect community (Ryszkowski and Karg 1977). In the rapeseed cultivations, Meligethes aeneus, which is also a pest, makes up more than 60% of the total aboveground biomass of the insect community (Ryszkowski and Karg 1986). Cereal cultivations have increasing populations of aphids and Lema melanopa because of the increasing trend of domination of cereals in crop rotation in Poland. Agricultural measures influence survival of particular groups of animals in different ways. There are numerous publications discussing reactions of particular animal populations to pesticides, fertilizers, ploughing, drainage, and other measures (Lowrance et al. 1984, Mills and Alley 1973, Tischler 1965, Braman and Pendley 1993, Tucker and Heath 1994, Goh Hyun Gwan et al. 1995, Lopez Fando and Bello 1995, Edwards and Bohlen 1996, Hu Feng et al. 1997, Ellsbury et al. 1998, Krooss and Schaefer 1998, Heath and Evans 2000). According to a thorough review of literature by Karg and Ryszkowski (1996), agricultural measures do not significantly impoverish Protozoa, Enchytraeidae, or Collembola. However, that finding does not mean that these groups are immune to agricultural influences. Some species show decreased numbers while others can increase their abundance. For example, Collembola in cultivated fields are represented by a fewer number of species and display large variation over time and low stability of species composition, but their long-term density is similar to that observed in forests or grasslands, with the exception of that found in some forests rich in litter. Similar results were recently published by Alvarez et al. (2001) indicating changes in particular species densities but no significant differences in total Collembola assemblages in organic, integrated, and conventional farming systems. Protozoa also show significant density fluctuations. Paprocki (1992) has shown a statistically significant correlation between soil humidity, the content of organic matter in soil, and the density of Protozoa. Nevertheless, comparisons of different estimates of the Protozoa population density shows that their abundance in cultivated fields is similar to that in forest and meadow ecosystems. There are even indications that tillage stimulates their abundance. Groups suppressed by agricultural measures include nematodes, earthworms, mites, spiders, and winged insects. Especially dramatic reduction in density and species composition is observed in earthworms, mites, and winged insects. Attempts to explain the causes responsible for invertebrate elimination from cultivated fields indicate an interplay of various factors rather than a single agent. For example, the direct, immediate effects of agrochemicals on insect populations are often clearly visible, but ecological long-term effects depend not only on their application, but to an even higher extent on crop rotation pattern, soil characteristics, and climatic and habitat conditions, as well as on biological characteristics of the species in question (Good and Giller 1991, Foissner 1992, Koehler 1992, Kreuter

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1995, Castro et al. 1996, Weber et al. 1997). Majority of earthworm populations are eradicated from cultivated fields because of lack of litter accumulation and frequent ploughing, that is by change of abiotic and food conditions than by application of agrochemicals with probable exception of fungicides (Paoletti 1988, Tucker 1992, Edwards and Bohlen 1996, Makulec 1997). Landscape structure diversity also has an important influence on the persistence of animals under agricultural stress, as discussed below.

ABUNDANCE AND DIVERSITY OF ANIMAL COMMUNITIES IN AN AGRICULTURAL LANDSCAPE Two aspects of landscape structure influence on animal communities can be distinguished. Distribution of species in the landscape reflects their adaptation to habitat conditions, e.g., some species can live in forest but not in grassland. Dispersion of animals from refuge sites can compensate for the losses caused by agricultural measures in a particular field. Thus, for example, in the Turew landscape the highest abundance as well as species diversity of earthworms was found in meadows (Table 8.9). Meadows or shelterbelts in the landscape result, therefore, in high diversity of those animals. Dominance of older specimens in cultivated fields, in contrast to meadows, could be explained by limited reproduction in the soil of agroecosystems and migration of observed mature individuals in fields from refuge sites such as meadows or shelterbelts. A similar situation is observed in other groups of animals. Thus, the number of Thysanoptera species in the whole Turew landscape amounts to 41, while in cultivated fields 13 to 18 species can be found (D. Szeflin´ ska, personal communication). Very high densities of Thysanoptera populations are recorded in cereal cultivations, although their species diversity is low (Table 8.10). This is the Table 8.9 Distribution of Earthworms in the Turew Landscape Cultivated Fields Rapeseed Wheat Alfalfa

Habitat Density of individuals·m Biomass g l.w.·m–2 Number of species

–2

8.7 2.2 4

10.0 3.8 3

23.8 5.5 2

Meadow

Shelterbelt

74.0 15.2 7

15.0 7.7 4

Source: Modified after Ryl 1984, Karg and Ryszkowski 1996. Table 8.10 Density and the Number of Thysanoptera Species in Turew Agricultural Landscape Ecosystem Cereals Maize Alfalfa Meadow Shelterbelts

Density Individuals·m–2 192.3 46.3 37.2 677.1 104.0

Number of Species

References

16 13 18 18 21

Szeflin´ ska, personal communication Szeflin´ ska, personal communication Szeflin´ ska 1996 Szeflin´ ska 1996 Szeflin´ ska, personal communication

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Table 8.11 Mean Annual Density and Biomass of Enchytraeidae in Soil of Various Ecosystems in the Turew Landscape Cultivation

Number of Estimates

Density Individuals·m–2

4 3 4 7 4 5 2 5 4

2000 2400 6450 3700 3900 8000 8400 8800 9700

Maize Spring cereals Winter crops Alfalfa Sugar beets Potatoes Road side Meadows Shelterbelts

Biomass mg d.w.·m–2 46.8 84.6 180.0 127.8 93.6 225.0 — 241.2 —

Source: Ryl 1977, 1980.

Table 8.12 Biomass of Aboveground Insects in the Agricultural Landscape of Turew Agroecosystem

Number of Estimates

Mean Year-long Biomass mg·m–2 Dry Weight

All spring cereals All rows crops All winter cereals Rapeseed Alfalfa Meadows

13 13 10 5 11 8

11 20 21 28 36 45

Source: Karg and Ryszkowski 1996.

result of increasing contribution of cereals in rotation pattern. A quite different pattern of distribution of Enchytraeidae is observed. In cultivations of crops for which manure was used, such as potatoes, the density and biomass of those animals are comparable to those in meadow or shelterbelt habitats (Table 8.11). Total biomass of aboveground insects reaches highest values in agroecosystems subjected to the smallest agricultural stress. Comparison of densities of total insect communities between different ecosystems is meaningless because of great differences in body weights in various species (from 0.002 mg d.w. per ind. to 750 mg d.w. per ind.). In meadows, the mean year-long standing biomass was estimated at 45 mg m–2, which is four times larger than biomass observed in spring cereals (Table 8.12). Using the same method of quick-trap sampling as used in the Turew landscape, aboveground insect fauna was studied in Romania, Italy, and Russia (Ryszkowski et al. 1993). In all the cases studied, a statistically significant impoverishment of the aboveground insect communities was observed in annual crops as opposed to grasslands (Table 8.13).

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Table 8.13 Mean Biomass of Aboveground Insects in Annual Crops and Grasslands in Different Regions of Europe (mg·m–2 dry weight) Country

Annual Crop

Grassland

Poland Italy Russia Romania

39.4 63.7 47.2 240.1

45.2 92.3 149.1 279.3

Source: Karg and Ryszkowski 1996.

The differences in the levels of mean standing biomass among countries to some extent reflect the adaptation of insects to prevailing environmental (climatic) conditions. The taxonomic structure of the insect community in the southern regions of Europe is characterized by the domination of large-sized Orthoptera species, which make up 60% of the total mean biomass in Romania and 48% in Italy. In Poland and Russia, Diptera, which are much smaller than Orthoptera dominate. Nevertheless, in all situations, lower biomass was observed in annual crops in comparison to grasslands. Flying insects in the Turew landscape were sampled by catching them in nets fixed at various heights on motorcycle (Karg 1980). The distribution of flying insects over the whole landscape could be evaluated in a very short time span (e.g., during one day) by this method. Analyzing records of flying insect distribution in all habitats of the Turew landscape, it is possible to distinguish three groups of habitats (Karg and Ryszkowski 1996). To the first group belong villages and spring crops in which the abundance of flying insects is very low. The average season-long biomass per one cubic meter of air in these habitats varied from 0.10 to 0.13 mg of dry weight. The second category of habitats consists of winter crops and perennial crops with biomass ranging from 0.21 to 0.25 mg of dry weight. The highest biomass, ranging from 0.26 to 0.29 mg dry weight, was found in meadows, shelterbelts, and afforestations. Taking into account the whole landscape, one can detect high taxonomic diversity of the insect community in mosaic landscapes. Of a total 3483 samples, Karg (1989) distinguished 172 taxonomic families from 18 orders of insects. Animal species of the Turew mosaic landscape make a considerable contribution to the faunistic lists of the region and even the country.* For instance, despite a relatively poor water network in the studied area, preservation of small mid-field water bodies allows for the appearance of 36 dragon fly species (Odonata), 50% of the country list, 40 species of water bugs (Heteroptera), 80% of the total province list, and 90 water beetle species (Coleoptera), 62% of the province list. Among the * *Ba l azy S., personal communication; Banaszak 1983; Bauerowa Z., Berger 1987, personal communication; Kaczmarek S., personal communication; Karg J., personal communication; Luczak 1979; Wasilewska 1979; Mielewczyk S., personal communication; Ryl 1977, 1984; Kasprzak and Ryl 1978; Rybacki M., personal communication; Ryszkowski 1982.)

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Table 8.14 A Comparison of Aboveground Insect Communities in Mosaic and Uniform Agricultural Landscapes Characteristics Mean number of families Mean density (ind/m2) Mean biomass (mg d.w./m2)

Landscape Mosaic Uniform 59.6 61.9 55.0

49.4 40.7 40.3

Statistical Significance P < 0.001 P < 0.01 P < 0.05

Source: Karg and Ryszkowski 1996.

terrestrial insects in the superfamily of bees (Apoidea), 258 species were recognized making 80% of the province list. More than 40 species of bark-beetles (Scolytidae) occur, about 70% of species list recorded in the province. Among Thysanoptera, 41 species were recorded. More than 600 species of Lepidoptera were identified. Earthworms (Lumbricidae) are represented by at least 7 species, Enchytraeidae by 16 species, nematodes by 40 species, spiders by 49, and Acarina by 216 species. Vertebrates are represented by 12 species of amphibia, 4 reptiles, 119 birds, and 47 mammals. Recorded terrestrial vertebrate species in the Turew mosaic landscape make up almost 100% of the province list with the exception of birds, which make up 62% of the regional list for breeding species. The above data clearly indicate that changes in the land-use pattern of a landscape have an enormous effect on density, biomass, and taxonomic diversity of animals. An increase of area under cereal cultivation will lead to overall impoverishment of animal resources in the landscape. This process is under way presently in Poland because of ongoing simplification of crop rotation patterns in favor of cereals. The area under cereal cultivation is currently 31.9% of the total territory of the country. Existence of numerous refuges for animals from which they can disperse into cultivated fields plays an important role in the survival of many species of animals. Analyzing the same cultivations in two types of landscapes showed that in the mosaic landscape not only density and biomass but also taxonomic diversity are greater than in a uniform landscape composed mainly of cultivated fields (Table 8.14). A similar relationship between the structure of landscape and the richness of aboveground insect communities was found by Karg (1997) in the northwest region of France (vinicity of Soissons). Higher biomass and taxonomic diversity was observed in mosaic agricultural landscapes than in uniform ones. Both Turew landscapes under investigation were situated close to each other (about 10 km apart), and the intensity of field cultivation (fertilizers, tillage) and application of pesticides were similar. The results show that 20% higher diversity of insect community could be maintained in a mosaic agricultural landscape than in a uniform one, despite intensive agriculture. Dispersion of insects from refuge sites increases their diversity in cultivated fields. The possibility of autumn colonization of the cultivated fields covered with growing plants increases the diversity of biota in cultivated fields. Winter crops as well as alfalfa cultivations show a higher taxonomic diversity than do spring crops (Table 8.15). The dispersion of insects from refuge sites into adjoining fields increases the abundance of all main trophic

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Table 8.15 Taxonomic Diversity of Aboveground Insect Communities in Uniform and Mosaic Landscapes — Number of Families in Particular Crops Number of Estimates

Crop Spring crops Oats Barley Maize Winter crops Wheat Perennial crops Alfalfa

Landscape Uniform Mosaic

1 6 6

48 61 65

56 65 77

5

90

121

11

100

121

Table 8.16 Mean Biomass (mg d.w.·m–2) and Its Share Indicated as Percentage (in parentheses) of Main Trophic Groups of Aboveground Insect Communities Located in Mosaic and Uniform Agricultural Landscapes Trophic Group

Cereal Crops in Landscape Mosaic Uniform

Herbivores 16.3 (44.5) Saprovores 8.4 (22.9) Predators 10.5 (28.8) Parasites 1.4 (3.8) Total

Sugar Beets in Landscape Mosaic Uniform

Alfalfa in Landscape Mosaic Uniform

9.5 (45.7) 23.1 (45.7) 19.4 (53.1) 48.7 (55.5) 33.8 (55.9) 5.2 (25.0) 11.1 (22.0) 7.0 (19.1) 20.0 (22.8) 15.7 (25.9) 5.4 (26.0) 13.8 (27.4) 8.5 (23.4) 13.9 (15.9) 7.7 (12.7) 0.7 (3.3) 2.5 (4.9) 1.6 (4.4) 5.1 (5.8) 3.3 (5.5)

36.6 (100.0) 20.8 (100.0) 50.5 (100.0) 36.5 (100.0) 87.7 (100.0) 60.5 (100.0)

groups. Almost two times more standing biomass of predators can be observed in fields located in mosaic landscape than in uniform agricultural landscape devoid of refuge sites (Table 8.16). Predatory and parasitic species of insects disperse from refuge sites and populate cultivated fields, enhancing the biological control of herbivorous populations. Taking the ratio of total standing biomass of herbivores and saprovores to total standing biomass of predators and parasites as an index of predator pressure on prey populations one can infer that biological control is more effective in a mosaic landscape than in a uniform one. Although the intensity of predator pressure on prey varies in different types of cultivations, the trend is nevertheless consistent in all cases, showing that the lower biomass of herbivores and saprovores falls on biomass unit of predators and parasites in fields located in mosaic landscapes. The lower this ratio is, the higher is the pressure of predators on prey (Table 8.17). In studies carried out in Romania by the same method as in Turew (Ryszkowski et al. 1993), the range of standing biomass of aboveground insects was estimated from 73.1 mg d.w.·m–2 (alfalfa) to 375.9 mg d.w.·m–2 (barley) in uniform agricultural landscape as compared to 100.8 mg d.w.·m–2 (sugar beet) to 584.0 mg d.w.·m–2 (barley) in mosaic landscapes. On average, the insect biomass was 56% higher in the mosaic landscape than in the uniform one (Table 8.18).

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Table 8.17 Index of Predator Pressure on Prey Populations Measured as the Ratio of Herbivores and Saprovores (prey) Standing Biomass (mg d.w.·m–2) to Predators and Parasites (predator) Biomass Kind of Landscape Prey Predator Predator pressure

Cereal Crops in Landscape Mosaic Uniform 24.7 11.9 2.1

14.7 6.1 2.4

Sugar Beets in Landscape Mosaic Uniform 34.2 16.3 2.1

26.4 10.1 2.6

Alfalfa in Landscape Mosaic Uniform 68.7 19.0 3.6

49.5 11.0 4.5

Table 8.18 Mean Biomass (mg d.w.·m–2) of Aboveground Insects in Uniform and Mosaic Landscapes in Romania Cultivation

Wheat

Barley

Maize

Sugar Beet

Alfalfa

Mean

Uniform landscape Mosaic landscape

98.7 101.2

375.9 584.0

83.3 174.5

111.5 100.8

73.0 199.2

148.5 231.9

Source: Modified from Ryszkowski et al. 1993.

The fields in the mosaic landscape were small and refuge sites covered about 12% of the studied area. In a uniform landscape there were no shelter habitats for a few kilometers from the studied fields. Crop rotation was also very simplified, showing in many cases of cereal cultivation almost continuous cropping of the same cultivar. Under such conditions, no correlation was found between predator and parasitic biomass and their potential prey (herbivores and saprovores). The pests to crops, such as Eurygaster integriceps (Heteroptera), had very high biomass and species from the Iassidae and Chysomelidae families had very high herbivore biomass in relation to existing predators. In such cases of very high uniformity of the agricultural landscape, the effectiveness of biological control is very small. The range of field penetration by various insects is differentiated, and therefore much higher densities of predatory forms are observed close to the refuge site than in the middle of a field (Thomas et al. 1991, Karg and Kundzewicz 1992, Karg and Szeflin´ ska 1996). Studies on aphids and their predators clearly illustrate that point (Figure 8.2). Aphids that overwinter in shelterbelts show an almost exponential decline in densities as the distance increases from shelterbelts. Their distribution in the field is mimicked by predators (Syrphidae). In the ecotone zone (up to 20 m from the shelterbelt) where densities of aphids were high, eight species of Syrphidae as well as 3.5-fold higher densities of their pupae were observed in contrast to three species and much lower pupal densities recorded in the middle of the field located 50 to 100 m from the shelterbelt. In addition, Chalcidoidea and Ichneumonidae (10 species) parasites to Syrphidae showed threefold higher invasion rates of their pupae close to shelterbelt than that in the middle of the field (Karg and Szeflin´ ska 1996). The results of the long-term, complex studies in the Turew agricultural landscape indicate that impoverishment of biota caused by agriculture could be modified if diversified landscape structures are maintained or introduced. The survival of the

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300

3.0

250

2.5

200

2.0

150

1.5

100

1.0

50

0.5

0 0

20

40

60

80

100

density of Syrphids pupae (ind.m-2)

density of aphids colonies per m-2

INFLUENCE OF LANDSCAPE MOSAIC STRUCTURE

0.0 120

distance from shelterbelt aphids colonies Figure 8.2

Syrphids pupae

Aphids and predatory Syrphids in relation to distance from shelterbelt.

rich animal communities depends on the presence of refuge sites. The habitats less disturbed by agricultural measures have better conditions for survival. The soils of the spring crops with the most frequent impacts of tillage activities usually show less abundance of animals than do winter crops and perennial crops, while the highest abundance is detected in meadows, shelterbelts, and mid-field forest patches. When a new shelterbelt is planted in a cultivated field, mobile animals, such as insects, very quickly colonize that newly created refuge site. In the first or second year a very high biomass, reaching 95.2 mg d.w.m–2, was observed. With the growing shelterbelt the diversity of the community increases, reaching after 5 to 7 years similar number of taxonomic families similar to that observed in 80-year-old shelterbelts (Figure 8.3). As early as in the first or second winter after planting of the shelterbelt, numerous insect communities can be found in its soil. The newly created refuge site in the landscape is populated very quickly by mobile animals such as insects. The biomass of hibernating insects in the newly planted shelterbelts is almost 15 times higher than that in a cultivated field (Table 8.19). After 3 to 5 years, the biomass of hibernating insects is only 3% lower than that of the older shelterbelt. That small difference is caused mainly by insect hibernation in litter. That result shows also the great negative effect of tillage activities (plowing, removal of plants, and others) on the overwintering success of insects in cultivated fields. It is also a clear demonstration of the great role of refuge sites for maintaining rich insect communities.

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70

number of families

60 50 40 30 20 10 0 1-2

3-4

5-7

80 years

age of shelterbelt Figure 8.3

Number of families of aboveground insects in shelterbelts of different age.

Table 8.19 Mean Biomass (dry weight mg·m–2) of Hibernating Insects (adult and larvae) in Young and Old Shelterbelts

Habitat Shelterbelt

Cultivated fields 50–100 m from shelterbelts

Age of Shelterbelt (years)

Location of Hibernating Insects Litter and Aboveground Soil (10 cm deep) Dry Plants Total Mg·m–2 Percent mg·m–2 Percent mg·m–2 Percent

1–2 3–5 80

681.3 842.9 845.8

88.9 86.5 83.7

—

51.9

100

85.1 131.9 164.8

11.1 13.5 16.3 —

766.4 974.8 1010.6

100.0 100.0 100.0

51.9

100

A well-developed mosaic pattern of shelterbelts provides refuge sites where animals can overwinter and find shelter from harmful agricultural measures such as the application of pesticides. The fields where animals were eliminated by harmful agents can be recolonized from unaffected refuges situated in the mosaic landscape. Thus one can suppose that the main factors counteracting biodiversity decline caused by agriculture are the mosaic structure of landscape and dispersal properties of species. Successful biodiversity protection programs in agricultural landscapes should consider the size and connectivity of refuges, requirements for breeding, food acquisition, and dispersal potential of species. Rich breeding communities of birds are found in the mosaic agricultural landscape. In a 13.8 km2-area of mosaic Turew landscape, Kujawa (1996) identified

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35

350 y = 1.51x + 10.3 r=0.82, P<0.01

30 25

250 y = 15.7x + 82.6 r=0.93, P<0.001

200

20

150

15

100

10

50

5

Number of species

Density (pairs/100ha)

300

0

0 0

4

12

8

16

Afforested areas (%) Density Figure 8.4

Species number

Relation between afforested areas (%) and number of species and total bird density in the Turew agricultural landscape.

Table 8.20 Breeding Bird Communities in Various Mid-Field Afforestations Characteristics Number of species Mean number of species/ha Density (pairs·ha–1)

Tree Patches (N = 21)

Shelterbelts (N = 33)

Alleys (N = 20)

60 14.1 14.9

51 16.8 18.3

32 7.6 9.8

N – number of plots. Source: Ryszkowski, et al., 1999.

almost 80 species of breeding birds. The diversity of bird communities depends on the contribution of area under shelterbelts or afforestations in a total landscape territory (Kujawa 1996, Kujawa and Tryjanowski 2000). The density of birds in rural areas is also related to the proportion of area covered by afforestations (Figure 8.4). The share of area under afforestations in total landscape area is the most important factor influencing the richness of bird communities. The type of afforestation also influences diversity and density of bird communities (Table 8.20). In the afforestations analyzed, avian fauna is richest in tree patches and poorest in alleys (single row of trees along roads, ditches, etc.). Kujawa (1997) showed that the number of species and density of birds in various afforestations depends on the age of the tree stand, density of trees, and size of the stand. In the Turew landscape with a well-developed network of shelterbelts, forest patches, and alleys, the number of bird species increased from 44 to 51 over a period of 30 years (1964–1994) despite changes in agricultural technologies (Gromadzki 1970, Kujawa 2001). The

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density of the bird community did not change over that period. These results do not mean that there was no change in densities of particular species. As the trees got older and more tree holes appeared, the density of species breeding in tree holes increased while the density of species relying more on cultivated fields (feeding or nesting there) decreased. Nevertheless, the density of the total community was stable over the period of 30 years. The change of trees’ age in the structure has important bearing on bird diversity and abundance. The planted shelterbelts are populated in the first or second year by all species that can find suitable niches for breeding there. In the case of such a young shelterbelt, the bird breeding community can be composed only by species nesting on the ground or in strata of very low vegetation. Therefore, the young shelterbelts in the Turew landscape can be inhabited by only 20 to 25 species, and not by another 45 to 50 species that require tree holes or higher strata of trees for nesting. If the niche requirements of species are not known, one can reach the wrong conclusion that the process of bird community settlement in shelterbelts is slow because only some of the species characteristic of shelterbelts appear in the first year after tree planting. In reality, due to bird’s powerful means of movement, they populate new habitats in the landscape as soon as new niches suitable for them appear. Probably the same interpretation applies in the case of insects populating newly planted shelterbelts, but their specific niche requirements are poorly known. The importance of shelterbelts as well as other nonarable habitats of agricultural landscape to bird species diversity and abundance has been demonstrated in many studies (see, for example, Green et al. 1994, Best et al. 1995, Fuller et al. 2001, Jobin et al. 2001 among others). All these studies provide information complementary to studies reported on the Turew mosaic agricultural landscape indicating that shelterbelts provide important habitats for birds and, by that token, can counteract impoverishment of their communities in rural areas. Although some woodland species of birds do not inhabit shelterbelts, many of the other species survive well in agricultural landscapes due to introduction of shelterbelts. To this last category belong such endangered species as the red-backed shrike (Lanius collurio), great gray shrike (Lanius excubitor), ortolan bunting (Emberiza hortulana), and corn bunting (Miliaria calandra). These two last species nest on sheltered ground and need trees as singing posts. With a more complex structure of shelterbelt, more species can find suitable niches for breeding. Nevertheless, some woodland species do not nest in shelterbelts, for example, goshawk (Accipiter gentilis), hobby (Falco subbuteo), middle spotted woodpecker (Dendrocops medius), wood warbler (Phylloscopus sibilatrix), pied flycatcher (Ficedula hypoleuca), among others. That situation may change in the future with respect to some of them, as recently happened with prior shy species such as the raven (Corvus corax), crane (Grus grus), gray lag goose (Anser anser) which now use tree patches (raven) or small mid-field ponds and wetlands (cranes, geese) and feed in cultivated fields of the Turew landscape. Especially the raven has become a quite common bird frequently seen feeding in cultivated fields. Among mammals such adaptations to mosaic agricultural landscape are observed in species such as roe deer (Capreolus capreolus), wild boar (Sus scrofa), and badger (Meles meles). One has to remember that organisms evolve to

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changed environmental conditions although some are unable to adapt and therefore vanish. The mosaic agricultural landscape probably better facilitates adaptations to agriculture than does the open landscape composed only of large cultivated fields.

PROSPECTS FOR THE BIOLOGICAL DIVERSITY MANAGEMENT IN AGRICULTURAL LANDSCAPES The Convention on Biological Diversity issued in 1992 at the World Summit in Rio de Janeiro strongly emphasized the need to stop and reverse the impoverishment of biological diversity. To overcome some operational shortcomings of this policy, which did clearly indicate the reciprocal links between protection of biodiversity and economic activities and did not recognize the importance of landscape ecological functions for species protection, the Pan-European Strategy for Biological and Landscape Diversity Strategy was adopted in 1995 by the Environment Ministers of the European Union. Two points are stressed clearly in this last document. The first one emphasizes initiatives promoting the integration of a biodiversity strategy with social and economic sectors. Successful living resource protection can be achieved when nature is not separated from or shielded against socioeconomical activities, but when human activities are reconciled with protection of biodiversity. The second one stresses the need not only for conservation but also for management of protected areas. Failure to manage structures and processes supporting biota results in unsuccessful execution of protection goals. The landscape approach, which embodies all provisions to sustain biological diversity, is thus gaining the utmost significance. This approach is becoming more important as humanity’s effects on nature increase and the area of the earth free from human interferences rapidly dwindles. The success of such a policy relies on the use of adequate tools, including the important role played by landscape ecology recognizing countryside structures, processes, and services enabling maintenance of the biological diversity in rural areas. This brief of the studies carried out in the Turew landscape demonstrated that diversification of the landscape structure is an important tool for the maintenance of rich plant and animal communities, including some protected or endangered species. The importance of nonarable habitats for biodiversity protection in the agricultural landscape was also recognized by other scientists. For example, Bunce and Hallam (1993) showed that various nonarable components of landscape are important reservoirs for protection of plant species because they can function as sources of propagules for recolonization of the agricultural landscapes. The enrichment effect of nonarable patches in landscape on populations or assemblages of taxonomically close species are well documentated in ornithological studies, examples of which were reported above. Distribution of insect species assemblages, especially beetles (Coleoptera), in shelterbelts, grass strips, field margins, and other similar components of landscape were studied also. Those studies indicated that nonarable refuge sites appear to be important habitats supporting abundant and diverse populations of insects (Burel 1996, Dennis et al. 1994, Kajak

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and Lukaszewicz 1994, Lagerlöf et al. 1992, Paoletti et al. 1992, Thomas and Marshall 1999, Varchola and Dunn 2001 and others). The important role of shelterbelts and other linear features of permanent vegetation was shown for dispersion of mammals in the landscape (Merriam 1991, Dobrowolski et al. 1993). Linear features of vegetation in the case of mobile species facilitate movement among habitat patches and ensure their recolonization. The interrelations between persistence of population and pattern of corridors connecting separate habitats were described by the metapopulation theory proposed by Opdam (1988). Thus it seems that the importance of the mosaic landscape structure for survival of plant or animal populations is evident, at least in the case of some populations, and implementation of nonarable patches into the open fields should be proposed for programs of nature protection. The studies carried out in the Turew landscape clearly show the impoverishment of the total set of animals in cultivated fields although some taxonomic groups, such as Protozoa, Enchytraeidae, and Collembola, do not show distinct changes under pressure of agriculture. Herbivores are more numerous and some species, such as crop pests (e.g., Colorado beetles [Leptinotarsa decemlineata] in potato cultivations), may even achieve the level of 84% of total aboveground insect biomass (Ryszkowski and Karg 1977). With that background, it is clearly seen that when agricultural landscape is properly managed in a mosaic, losses of biodiversity can to some extent be counteracted. The introduced refuge sites, such as newly planted shelterbelts, are very quickly populated by many species — an important finding for successful programs of biodiversity restoration. In the case of landscapes composed only of large cultivated fields, herbivores are almost free from predator pressure (Ryszkowski et al. 1993). With increasing eradication of refuge sites, an important functional change is observed among soil invertebrates; species having smaller body sizes, higher reproduction success, and shorter developmental cycles are dominating. This finding means that energetic costs of maintenance of soil animal community is higher than in the mosaic landscape, and outbreaks of population densities can appear more frequently in the uniform agricultural landscape. Plant diversity in agricultural landscape contributes to overall diversity not only by its modifications of habitat conditions, enabling persistence of other plant species, but also by its strong influence on animal diversity. A complicated structure of shelterbelt not only consists of a diversified plant community but also harbors more animal species than does a cultivated field. Long-term studies on the biota in uniform and in diversified agricultural landscapes show that the mosaic character of landscape plays an important role in maintaining the richness of plant and animal communities. This function is a result of the existence of numerous refuges for plants and animals and for their potential dispersal. The mosaic agricultural landscapes can therefore support biodiversity protection in reserves, national parks, and other territorial forms of nature conservancy that are usually surrounded by cultivated fields. The strategy of biodiversity protection should aim at elaboration of guidelines reconciling agricultural production with landscape management, encouraging its diversity by maintenance of nonarable components. The achievement of landscape ecology became, therefore, one of the most important theoretical pillars for conservancy of biological diversity.

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Varchola J. M., Dunn J. P. 2001. Influence of hedgerow and grassy field borders on ground beetle (Coleoptera: Carabidae) activity in fields of corn. Agric. Ecosystems Environ. 83: 153–163. Vitousek P. M., Mooney H. A., Lubchenco J., Melillo J. M. 1997. Human domination of earth’s ecosystems. Science 277: 494–499. Warcholin´ ska A.U. 1976. Segetal flora of Piotrowska Plain (Central Polish Lowland Mesoregion) [in Polish]. Zeszyty Naukowe Uniwersytetu Lódzkiego 8: 63–95. Warcholin´ ska A.U. 1983. Materials to the segetal flora of the south-eastern part of the Nizina Po l udniowowielkopolska (Southern Wielkopolska Lowland) [in Polish]. Badan´ ia Fizjograficzne nad Polska˛ Zachodnia˛ , B 34: 103–129. Warcholin´ ska A. U. 1986/87. A list of endangered segetal plant species in Central Poland [in Polish]. Fragmenta Floristica et Geobotanica 31–32: 225–231. Warcholin´ ska A.U. 1992. Changes of segetal vegetation of Southern Mazovian Elevation in 1971–1990 years [in Polish]. Zeszyty Naukowe Akademii Rolniczej w Krakowie 33: 157–170. Warcholin´ ska A.U. 1997. Flora and segetal vegetation of the Sulejów Nature Park. Part I. Segetal vegetation [in Polish]. Acta Agrobotanica 50: 163–180. Warcholin´ ska A.U., Mazurkiewicz U. 1999. Segetal flora of Inow l ódz´ [in Polish]. Acta Agrobotanica, 52: 167–182. Warcholin´ ska A.U., Pote˛ bska A. 1998. Segetal flota of Be˛ dkowo [in Polish]. Acta Agrobotanica, 51: 63–80. Warwick S. I. 1991. Herbicide resistance in weedy plants physiology and population biology. Ann. Rev. Ecol. Syst. 22: 95–114. Wasilewska L. 1979. The structure and function of soil nematode communities in natural ecosystems and agrocenoses. Pol. Ecol. Stud. 5: 97–145. Weber G., Franzen J., Buchs W. 1997. Beneficial diptera in field crops with different inputs of pesticides and fertilizers. Entomological research in organic agriculture. Selected papers from the European Workshop, Austrian Federal Ministry of Science and Research. Biol. Agric. and Horticul. 15: 109–122. Wika S. 1986. Geobotanical problems of the central part of the Cracow-Weilun´ Upland [in Polish]. Prace Naukowe Uniwersytetu S´ la˛ skiego w Katowicach 815, 156 pp. Wilson E. O., Peter F. M. (Eds.). 1988. Biodiversity. National Academy Press. Washington, D.C. 521 pp. Zarzycki K., Szela˛ g Z. 1992. Red list of threatened vascular plants in Poland. In List of Threatened Plants in Poland. K. Zarzycki, W. Wojewoda, Z. Heinrich (Eds.). Instytut Botaniki im Szafera PAN. Kraków: 87–98. · Zukowski W., Jackowiak B. 1995. List of endangered and threatened vascular plants in Western Pomerania and Wielkopolska (Great Poland). In Endangered and Threatened · Vascular Plants of Western Pomerania and Wielkopolska. W. Zukowski, B. Jackowiak (Eds.). Prace Zak l adu Taksonomii Ros´ lin UAM. Poznan´ 3: 9–96. · Zukowski W., Latowski K., Jackowiak B., Chmiel J. 1995. The Vascular Plants of Wielkopolska National Park [in Polish]. Bogucki Wydawnictwo Naukowe. Poznan´ . 229 pp.

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CHAPTER

9

Field Boundary Habitats for Wildlife, Crop, and Environmental Protection Jon Marshall, Jacques Baudry, Françoise Burel, Wouter Joenje, Bärbel Gerowitt, Maurizio Paoletti, George Thomas, David Kleijn, Didier Le Coeur, and Camilla Moonen

CONTENTS Introduction............................................................................................................220 Methods..................................................................................................................223 Ecological Impacts of Enlarged Field Boundaries......................................223 Factors Affecting Flora Diversity in Field Margin Systems in European Landscapes .................................................................................225 Landscape Scale Studies..................................................................225 Herbaceous Plant Diversity on Two Farms, with and without Sown Grass Strips, in Wiltshire, U.K. ...........................................226 Results....................................................................................................................227 Ecological Impacts of Enlarged Field Boundaries — Flora.......................227 Development of the Flora in Margin Strips in Different European Countries ........................................................................227 Impacts of Fertilizer and Herbicide on the Diversity of Sown Margin Flora ...................................................................................229 Ecological Impacts of Enlarged Field Boundaries — Fauna......................230 Single Year, Single Site Comparisons between Countries — Activity-Density and Diversity: Comparing Carabid Diversity in France, the U.K., and the Netherlands ......................................230 Comparisons of Invertebrate Abundance and Composition in the Hedge, Sown Plots, Crop Edge and Field by Suction Sampling in the U.K. .....................................................................231 Field Margins as Overwintering Sites for Invertebrates .............................231

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Spatial Behavior of Ground Beetles............................................................232 Factors Affecting Flora Diversity in Field Margin Systems in European Landscapes..................................................................................................234 Landscape Scale Studies..................................................................234 Herbaceous Plant Diversity on Two Farms, with and without Sown Grass Strips, in Wiltshire, U.K. ...........................................235 Discussion ..............................................................................................................239 Field Margins in European Landscapes ......................................................239 Processes Affecting Field Margins ..................................................240 Introducing Vegetation Strips at Field Edges ..................................240 Invertebrates of Field Edges ............................................................241 Managing Field Margins..................................................................242 Conclusions............................................................................................................243 Recommendations..................................................................................................243 Acknowledgments..................................................................................................244 References..............................................................................................................244

INTRODUCTION Agricultural landscapes in Europe are diverse, reflecting their geology, geographical relief, history, and intensity of management. They vary from small-scale, enclosed landscapes, such as the bocage (INRA, 1976), to open prairie types. Within these landscapes, the majority of the land is farmed. Before expansion of the European Union, the agricultural area of 127.32 million ha comprised at least 56% of the land surface. In some countries, a much higher percentage of land is managed or farmed. Within all farmed landscapes, fields are bounded by seminatural margin habitats. The influences of farming practices are not limited to the cropping areas within agricultural landscapes. Likewise, the areas of unfarmed or noncrop land, which form the framework of agricultural land, can have important influences on adjacent fields. Agriculture does not occur in isolation but interacts with these areas, a fact underlined by the problems now being encountered with ground- and surfacewater contamination by nutrients and pesticides from agriculture. Within agricultural landscapes, crop and noncrop features comprise a diversity of habitats. These include arable land, grassland habitats that range from acid to alkaline communities with varying moisture regimes, aquatic, and riparian zones and a variety of boundary and woodland types. The mosaic structure of the farm landscape and its topography give the regional character to most of Europe. Often, these seminatural areas are important refuges for farmland wildlife, including plants and invertebrate and vertebrate animals, some of which may be of agronomic benefit. The conservation of such species may be best achieved by harmonizing land management toward a plurality of objectives, including agricultural production and wildlife conservation. Field margins form the commonest interface between intensive agriculture and the wider environment and are often the commonest component of seminatural areas on farms. The rapid change from one habitat to another forms an

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Figure 9.1

221

The principal components of an arable field margin. (After Greaves and Marshall, 1987.)

ecotone, which may support particular species and may buffer the movement of agrochemicals, water, and soil erosion. Thus the field margin has agricultural, environmental and wildlife attributes, aspects of which may be exploited for more sustainable production and for environmental benefits (Marshall, 1993). Field margins, as defined by Greaves and Marshall (1987), comprise the field boundary which usually has a structure, such as a hedge, wall, grass bank, or ditch, often a boundary strip, which may be a farm track or sown vegetation strip, and the crop edge (Figure 9.1). The margin is a seminatural habitat, often a hedgerow in the U.K. (Marshall, 1988; Pollard et al., 1974), that contains a range of plant communities. These can include cornfield weeds, grassland, tall herb, scrub, woodland and aquatic communities and often combinations of these. Traditionally, the field margin has agricultural functions, notably impoundment of animals and field delineation. Under intensive arable production, such functions are less important to landowners, and many margins and hedges have been removed since the Second World War (Pollard et al., 1974). The rates of hedge removal declined in the U.K. in the 1970s, and it was not until the Countryside Survey 1990 (Barr et al., 1991; Barr et al., 1993) that more recent data has become available. These indicate that many hedges, particularly in livestock areas, are losing their structure and, as a result, their value to agriculture, wildlife and landscape. Changes within arable farming have also resulted in reduced diversity of arable weeds, such that many cornfield flowers are rare and even threatened by extinction (Wilson, 1993). Long-running census and

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atlas programs of the British Trust for Ornithology (BTO) have identified major decline in population size and range of farmland birds (Fuller et al., 1995). Many species, notably gray partridge, song thrush, tree sparrow, linnet, bullfinch, reed bunting and corn bunting, utilize cereal field margins to a large extent, but show marked declines, probably reflecting major changes in arable farming practice. The view that the linear elements of seminatural habitat in farmland (field margins) provide refuge habitat for many wildlife species (Baudry, 1988) has been confirmed by land use studies in the U.K. (Countryside Survey 1990 and 2000; Barr et al., 1993; Haines-Young et al., 2000). In lowland Europe, field margins are the most diverse elements in the landscape for flora (Burel, 1996; Burel and Baudry, 1990). Birds also utilize margins and adjacent crops and are affected by structure and cropping patterns (Green et al., 1994; Parish et al., 1995). The network of hedgerows also supports invertebrates (Morris and Webb, 1987), such as beetles (Burel, 1989), some of which migrate into cereal crops in spring and feed on cereal aphids (Wratten, 1988; Paoletti, 2001). Polyphagous predators of spider mites can also be effective in landscapes with a hedgerow network in Italy (Paoletti and Lorenzoni, 1989). Thus margins are of particular importance for biodiversity. The interactions between fields and their margins occur in both directions. Farming operations can affect the hedgerow, for example by the addition of fertilizer, while the hedge may affect adjacent crops (Marshall and Smith, 1987; Tsiouris and Marshall, 1998). The perception that weed species invade arable crops from the hedgerow has led to inappropriate management in some cases, notably application of broad-spectrum herbicides. Detailed studies indicate that most herbaceous plant species associated with field margins do not pose a threat as weeds (Marshall, 1989), though a small number of species can invade adjacent crops. The proximity of the hedgerow to the field in arable cropping has led to many margins containing impoverished flora, reflecting eutrophication from fertilizer additions and disturbance from cultivations and pesticide drift. Techniques of manipulating the field edge to encourage diversity and ameliorate the adverse effects of adjacent farm operations have been studied in the U.K. (Marshall and Nowakowski, 1991; West and Marshall, 1996) and in Europe (Jörg, 1994). Within the crop edge, reduced pesticide application has been used to encourage rare arable weeds (Schumacher, 1987) and, as conservation headlands in the U.K., to increase populations of the gray partridge (Rands, 1985). The impacts of these initiatives on farmland birds as a whole is not clear, and neither are their effect on the range of flora of the field and margin. Farmers have viewed field margins as the origin of a range of problems within crop land. This was particularly the perception for weed species in the U.K., although pest and disease spread have also been cited. In contrast to farmers’ perceptions, the general public views field margins, particularly hedgerows, as important elements in the landscape. The desire to retain traditional farm landscapes and the biodiversity within them is one reason for the designation of environmentally sensitive areas (ESAs) within which traditional farming practices are encouraged. The overall objective of this project was to understand some of the major factors affecting the diversity of margins and to understand some of the important processes at work across the field boundary ecotone, with the aim of exploiting these by

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appropriate management for the benefit of farm wildlife, environmental protection, and sustainable crop production, thus optimizing the use of biological resources on farms. As part of the European Communities Third Framework Programme, a research consortium from five countries investigated the ecology and management of field margins at a range of spatial scales. This chapter summarizes some of the results of this research program (Marshall, 1997). Specific objectives were: • To determine the function of field margins in the maintenance of plant and animal communities and the movement of nutrients and pesticides within different community landscape structures and farming systems • To identify the means of (1) enhancing biological diversity along fields for wildlife conservation and integrated crop protection and (2) exploiting any buffering actions to farm operations • To develop a generalized model description of the field margin ecotone, including transfer of materials (nutrient, biomass, agrochemicals) and organisms

METHODS Ecological Impacts of Enlarged Field Boundaries The study aimed at determining (1) what relationship exists between vegetation development on an extended field boundary and the adjacent (original) boundary, (2) whether these relationships are consistent in contrasting boundary types in different countries, and (3) whether these relationships are consistent between naturally regenerating and grass-sown boundary strips. In spring 1993, field boundary plots were established next to existing field boundaries near Rennes (France), Wageningen (the Netherlands) and Bristol (U.K.). Similar plots were also established near Göttingen (Germany) and Padova (Italy). The plots were created by taking the outer 4 m of the crop edge out of production and either sowing it to Lolium perenne or letting it regenerate naturally. Plots were at least 8 m long. Thus in these plots, the pre-existing field boundary was broadened by 4 m. Stretches of regular field boundary served as control plots. Management in the original boundary remained as it was before the onset of the experiment, while the L. perenne sown plots (grass plots) and the plots left regenerating naturally (regeneration plots) were mown once a year in autumn with the cuttings being removed. Alternative seed mixtures, comprising a mixture of grasses and flowers or flowers, alone were included at some sites. In the original field boundary, 0.5 × 2 m permanent quadrats (PQ) were established next to each plot type. To relate distance from the original boundary to vegetational development in the new strip, each grass or regeneration plot had two PQs, one near the original field boundary and one near the arable field (Figure 9.2). Plant relevées in the PQs were made annually in June/July, and peak standing crop was sampled by cutting aboveground biomass of a 0.5 × 0.5 m quadrat on each side of the PQ. The samples were pooled and split into monocotyledonous species

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1 Boundary

2

3 Plot

4

5

Positions

Crop

0.5 m Permanent flora quadra

2m 0.5 m

0.5 m 12 m Pitfall traps

4m

Figure 9.2

Layout of a single boundary plot. Distances in meters. * = pitfall trap for fauna.

(monocots) and dicotyledonous species (dicots). Dry weight was determined after 24 h at 80°C. The fauna were assessed using pitfall trapping and Dietrich vacuum sampling from the vegetation during the summer. Two pitfall traps were placed approximately 0.5 m apart at each sampling site. The sampling positions were located in parallel rows aligned centrally with each of the field margin plots. Four positions were trapped: the hedgerow (H) or existing boundary (0.5 m from the sown plots); centrally within the sown plot (P); at the crop edge (E) adjacent to the plots (0.5 m from sown plots); and in the cropped area of the field (F)12 m from the plot edge. A total of 96 traps were thus used at each of the field sites in 12 rows of four sampling positions. Pitfall traps were partly filled with trapping fluid (25 ml detergent in 10l of 1:1 water:ethylene glycol antifreeze) to ensure drowning and preservation of captured invertebrates. D-vac sampling was performed in June. D-vac samples were taken from the hedge position, each of the field margin plot types, the crop edge adjacent to the plots, and 12 m within the field. Each sample comprised three subsamples of a 10- to 15-sec application of the D-vac head (area 0.1 m2). The D-vac net was 1.5 m long enabling tall vegetation to be sampled without crushing. The samples were placed in labeled plastic bags and stored in a freezer overnight before being transferred to 70% alcohol for preservation prior to identification and analysis. Detailed statistical analyses were made on the Carabidae (ground beetles). An assessment of invertebrates overwintering in field margin habitats was made at two U.K. sites where soil samples were taken after D-vac sampling of the standing vegetation. Samples were returned to the laboratory, and the invertebrates were extracted by hand from the soil, using a wet sieving technique. Fauna were identified to order or family. In the U.K., a detailed mark-recapture program was developed, using a grid of pitfall traps located on two sides of a wide hedgerow (Thomas, 1995; Thomas et al., 1998, 2001). The objective was to understand the spatial behavior of a number of ground beetle species. The traps were used dry and checked every 2 days for extended periods during one summer and autumn.

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Factors Affecting Flora Diversity in Field Margin Systems in European Landscapes Landscape Scale Studies The objective of the studies was to identify the major factors affecting the margin plant communities found in different landscapes and to provide an idea of the different landscape types at a regional scale and their interactions with linear boundary features. Extensive collections of field and cartographic data were made and analyses made using multivariate correspondence packages. The Bocage database was specially developed for the data, using the dBase IV program (Denis et al., 1995). The approach to data collecting was as follows: • Sample areas were selected at random from within, if possible, nationally identified land classes. • Within the chosen area, all margin units up to a minimum of 50 were surveyed. Each unit comprised a margin length of uniform aspect, usually an entire side of a field. • A relevée of the plant species present in the undisturbed margin area was made for the entire hedgerow (margin) length, using the five-point Tansley scale (r = rare; o = occasional; f = frequent; a = abundant; d = dominant), to give a semiquantitative measure of cover/abundance, and repeated on the other side of the margin. In addition, a second relevée of 25-m length of the margin selected at random was made. A third relevée of the weed flora present in the entire field was also made. • Information on field margin structure, management, size, and on adjacent crop area was also collected.

The flora of field boundaries in ten different farmed landscapes, from France, the Netherlands, and the U.K., were investigated. Data were collected from up to 50 field margins in each area of 50–100 ha, both from whole margins of variable length and from 25-m sections within each. The flora present in the ground, shrub and tree layers were recorded, together with data on the physical structure and orientation of the margin, the adjacent land use, and management of the boundary. These data were subjected to multivariate analyses (PCA, RDA, etc,) on a site basis (Jongman et al., 1995). Selected results from 25-m sections from four areas in the U.K. and France (Table 9.1) are reported below.

Table 9.1 Details of Areas Where Field Margin Flora Have Been Surveyed Country U.K. U.K. France France

Area

Landscape

Margins

Cossington, Somerset Corsham, Wiltshire Pleine-Fougères, Brittany Mont Saint Michel, Brittany

Grazing marsh/polder Mainly arable farm land Bocage, grassland Polder with arable land

Drainage channels, hedges Hedges Hedges Dikes and drainage channels

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Herbaceous Plant Diversity on Two Farms, with and without Sown Grass Strips, in Wiltshire, U.K. The objectives of this study were (1) to investigate differences in the herbaceous hedge-bottom vegetation of hedgerows with and without a sown strip between the hedge and the field; (2) to assess the effects of different agricultural practices, land use and boundary structure on the hedge-bottom vegetation; and (3) to show any succession of the hedge-bottom vegetation in coppiced hedges. The two farms were chosen for their different approach toward boundary management and for their homogeneity in geology, landscape structure, boundary structure and land use (Moonen and Marshall, 2001). The farms are about 200 ha each, and field size varies between 4 and 40 hectares, mainly occupied by cereals and oil-seed rape. Both are on fine silty clay soil over lithoskeletal chalk. The landscape is largely flat, but with chalk hills close by, and with most fields bordered by hedges. Boundaries on the Manor Farm are characterized by 2-m, 4-m, or 20-m wide sown grass and grasswildflower strips established between the hedge and the crop. Nine hedges were also coppiced and gapped-up under the former Hedgerow Incentive Scheme (Whelon, 1994). These rejuvenated hedges had been cut to the ground (coppiced) to encourage shrubs and the gaps planted with young hedging plants. Boundaries on Noland’s Farm are characterized by a 0.5-m sterile strip (Table 9.1) created with a broad-spectrum herbicide. Differences in agricultural practices between the two farms that are thought to influence the hedge-bottom vegetation are listed in Table 9.2. The vegetation of the hedge-bottom (excluding the sown strips) was assessed in 25-m long plots in the middle of a field edge, on either side of the hedge. Each side of the hedge was treated as a separate plot, in order to establish the effects of adjacent land use and management. The width of each plot varied with the width of the hedge and associated hedge bottom, excluding any sown strip. Vegetation was assessed using the five-point Tansley scale (1 = rare, 2 = occasional, 3 = frequent, 4 = abundant, 5 = dominant) (Tansley, 1935). Boundary structure, management and adjacent features were recorded according to standards described by Denis et al. (1994). Thus, every vegetation sample was associated with a set of 24 environmental variables, made up of five boundary structure variables, 11 management variables

Table 9.2 Differences in Agricultural Practices between Two Farms Noland’s Farm 0.5-m sterile strip between hedge and crop Hedge trimmed annually, cuttings left No coppicing or gapping up Hedge-bottom cut annually, cuttings left Hedge-bottom not treated with herbicides Granular fertilizer sprayed up to and into the hedge

Manor Farm 2- to 20-m wide sown strips between hedge and crop Hedge trimmed in alternate years Coppiced and gapped up Hedge-bottom cut every 3 years Local use of specific herbicides to control large weed patches, rarely done Liquid fertilizer applied by injection, no drift into hedge

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and eight adjacent features. On Noland’s Farm, 23 hedges were examined and 37 on the Manor Farm. As only one side of the hedge was sampled for some sites, there were 43 relevées on Noland’s Farm and 74 on Manor Farm. Following simple tabulation of the data, which comprised 117 relevées for 94 herbaceous and 24 environmental variables, and tests for differences in diversity and abundance between farms, the results were analyzed using multivariate statistics. Principal Component Analysis (PCA) and Redundancy Analysis (RDA) in combination with forward selection and an associated Monte-Carlo permutation test in CANOCO 4.0 (ter Braak, 1987a, 1987b, 1996) were used to assess differences in herbaceous species composition between the two farms. RDA reveals which environmental variables are responsible for those differences and indicates their relative importance. Ordination diagrams were created using CanoDraw 3.1 and CanoPost 1.0 programs. Stepwise linear regression of species richness with environmental variables was also conducted to test which variables influence species richness.

RESULTS Ecological Impacts of Enlarged Field Boundaries — Flora Development of the Flora in Margin Strips in Different European Countries Considering the margins in France, the Netherlands, and the U.K., the vegetation in the different original boundaries was characterized by a large number of the same species despite the fact that there were large differences in boundary types, soil types or even geographical latitude (Kleijn et al., 1998); 49, 59, and 45% of the species in the respective French, Dutch, and English strips were found in one or both of the other countries. None of the species encountered in any of the countries was rare and most species could be classified as common to extremely common. A comparison between PQ1 next to the control plots and PQ1 next to the grass and regeneration plots (thus buffered from the arable field by a 4-m wide strip of perennial vegetation) did not reveal any significant differences in the similarity index, species numbers, biomass production or abundance of any of the functional groups. Therefore, PQ1 next to the grass and regeneration plots can be considered representative for the field boundary in its original state. The vegetation in the original field boundary was highly dynamic. Species similarity of the vegetation in PQ1 between 1993 and the following 2 years ranged from 40 to 80%. In the newly established boundary plots, species similarity with the original field boundary in 1993 increased with time and decreased with distance from that boundary. However, similarity in the boundary plots never rose much above 40% in any country or year. Also, differences between grass and regeneration plots were insignificant. The initial species richness in the pre-existing boundary ranged from a mean of 8 species·m–2 in the Netherlands to about 13 in the U.K. (Figure 9.3a–c). In all three

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Figure 9.3

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Mean number of species (m–2) in the original boundary (PQ1) and the adjoining regeneration (shaded bars) and grass (unshaded bars) plots (PQ2 and PQ3). Significances are as in Figure 9.2. (a) France, n = 6; (b) the Netherlands, n = 9; (c) U.K. n = 9.

countries, species numbers diverged between the grass and the regeneration plots in 1994 but converged again in 1995 to the levels found in the original boundary (PQ1), most notably in France. In the Netherlands, only PQ3 in the regeneration plots had significantly higher numbers, and in the U.K. they consistently remained low in both PQs in the grass plots.

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In the Netherlands, mean total biomass production was consistently higher in regeneration plots compared with grass plots, while in the U.K. the mean grass plot yields were always higher than the yields in the regeneration plots. By 1995, however, differences between PQ position and plot type were not significant. In France, mean total biomass showed a tendency for increased production with increasing distance from the original boundary. Shading by the dense and tall hedgerow in the original boundary may have been the cause of this trend. Mean biomass production of dicotyledonous species showed a similar pattern in all three countries. In the boundary plots large and significant differences were found in 1994 between the grass (low yields) and the regeneration plots (high yields). These differences reduced in size in the following year to become insignificant in France, while in the Netherlands and the U.K. only the differences in the PQ3 position, although considerably decreased in size, remained significant. Biomass production of monocotyledonous species showed just the opposite pattern of the dicotyledonous species. Finally, in 1995 an extended perennial field boundary had developed which was primarily composed of a limited set of the species found in 1993 in the original boundary. At 0.5 m from the arable field (PQ3) in all three countries, a limited number of species (most notably, Agrostis stolonifera, Poa trivialis, Ranunculus repens and Trifolium repens) had become extremely abundant. In the new strip 63, 45, and 63% of the species in, respectively, France, the Netherlands, and the U.K., were found in at least one other country. Total species numbers encountered in the three countries showed a marked decline in France and the U.K. and a sharp increase in the Netherlands. The decline in France and the U.K. was primarily the result of a reduced number of annuals and dicotyledonous species. Most of the dicotyledonous species that were not encountered in the new boundary were woody or woodland species. In the Netherlands the increase in total species numbers was almost entirely caused by the increase in annual species. Where a diverse seed mixture had been sown, as in the U.K., the Netherlands, and Germany, plant species diversity was consistently higher where the most diverse seed mixture was sown (Gerowitt and Wildenhayn, 1997; Kleijn, 1997). This effect was also reported for a series of sown margin strips in three different areas and on three soil types in the U.K. (Marshall et al., 1998; West and Marshall, 1996, 1997; West et al., 1999). Nevertheless, there were circumstances where undesirable species, notably Cirsium arvense, could dominate introduced strips. This effect appears to be markedly reduced where grasses are sown (Smith et al., 1999; West et al., 1997). Impacts of Fertilizer and Herbicide on the Diversity of Sown Margin Flora An examination of the effects of fertilizer contamination and herbicide drift was made on sown plots on ex-arable land in the Netherlands. The data (Figure 9.4) show that fertilizer in particular has an adverse effect on plant species diversity. Herbicide drift also can reduce species diversity, though the effect is likely to be less and also is dependent on the active ingredient and its selectivity between species (Kleijn and Snoeijing, 1997).

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35

Number of species

30 25 20 15 10

0

Herbicide (fluroxypyr) dose (%)

5% (10 mg/ha/year)

5

10% (20 mg/ha/year)

0 0

25% (27.5 kg N/ha/year)

50% (100 mg/ha/year) 50% (55 kg N/ha/year)

Fertilizer dose (%) Figure 9.4

Mean number of plant species on plots treated in factorial combinations of fertilizer and herbicide.

Ecological Impacts of Enlarged Field Boundaries — Fauna Single Year, Single Site Comparisons between Countries — Activity-Density and Diversity: Comparing Carabid Diversity between France, the U.K., and the Netherlands A species list for a single site and single date (June, 1995) for three countries was developed. Of the 68 carabid species recorded from pitfall traps, 44 occurred in France, 33 in the U.K., and 21 in the Netherlands. Only 7 species were common to all three countries with 24 species appearing only in the French list, 14 only in the U.K. list, and 7 only in the Dutch list. Although sampling effort was similar for each data set, sampling strategies differed slightly among countries making strict comparisons difficult. The absence of a species from the list in one sample did not indicate an absence from the fauna. No significant differences were found among the countries (P = 0.57) and no significant interaction was found between country and plot type (P = 0.34). There was, however, a significant effect due to plot type (P = 0.004) with highest activitydensity in all three countries occurring in the arable plots, where the vegetation was typically more open. There was no significant effect due to country (P = 0.08) but a highly significant effect due to position (P < 0.001) with highest activity-density of total carabids in the crop and at the crop edge. There were significantly more carabids in the crop from the U.K. site compared with the Netherlands.

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Table 9.3 Abundance of Invertebrates at the Different Positions in Fields A and B Mean Number of Invertebrates per Sample Field A Field B Hedge Sown Field Margin Crop Edge Field

233.0 155.8 84.5 96.8

223.0 147.8 58.3 76.9

Table 9.4 Number of Taxa and Plant Species Present in Each Habitat Type Field Taxa Flora

20 2.9

Crop Edge Ecotone CL LP NR WF 23 6.7

22 9.7

23 6.7

25 9.3

CL

Field Margin Plots LP NR WF

26 4.0

28 8.7

29 12.0

29 10.2

Hedge 35 15.3

CL = arable; LP = Lolium perenne; NR = natural regeneration; WF = wild flowers.

Comparisons of Invertebrate Abundance and Composition in the Hedge, Sown Plots, Crop Edge, and Field by Suction Sampling in the U.K. A total of 21,176 invertebrates were collected. With this number of specimens, identification to species was impractical; identification was therefore restricted to order or family. The relative distribution and abundance of total invertebrates at different positions (hedge, margin, edge and field) was similar in both fields (Table 9.3). Highest densities were found in the hedge with densities approximately one third less in the sown margin. The lowest densities were at the crop edge ecotone where invertebrate numbers were one fourth to one third that found in the hedge. Invertebrate density in the field was slightly higher than that found at the crop edge. A total of 45 different taxa were identified in the whole sample. Although each high level taxon (order/family) is composed of several taxa at the level of genus or species, an indication of invertebrate diversity in the different habitat types is given by the number of taxa represented in the total sample from each location (Table 9.4). These results show a pattern similar to that demonstrated for total invertebrate abundance with fewest taxa (20) present in the field, slightly more at the crop edge (22 to 25), higher numbers of taxa in the sown plots (26 to 29), and highest in the hedge samples (35). These results provide evidence for a positive correlation between faunal and floral diversity. Field Margins as Overwintering Sites for Invertebrates The numbers of arthropods in the principal taxonomic groups were transformed to log10 (n+1) and the data from each field were analyzed separately by ANOVA.

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Mean [log10(n+1)] Numbers of Arthropods per Sample with Standard Errors of Differencea Carabid Adults Sig. Mean Diff.

Staphylinid Adults Sig. Mean Diff.

Coleopteran Larvae Sig. Mean Diff.

Other Adult Coleoptera Sig. Mean Diff.

Hemiptera Sig. Mean Diff.

Field 47 Field Cereal margin Natural regen. L. perenne Grass and flower Hedge SED (48df)

0.00 0.03 0.12 0.07 0.17 0.53 0.10

a a a a a b

0.03 0.00 0.05 0.07 0.00 1.35 0.07

a a a a a b

0.43 0.17 0.40 0.31 0.44 1.00 0.13

ab a ab ab b c

0.00 0.00 0.07 0.00 0.00 0.55 0.06

a a a a a b

0.00 0.00 0.00 0.00 0.00 0.00 0.00

a a a a a a

Isopoda Dipteran Adults Dipteran Larvae Dermaptera and Myriapoda Araneae Sig. Sig. Sig. Sig. Sig. Mean Diff. Mean Diff. Mean Diff. Mean Diff. Mean Diff. Field 47 Field Cereal margin Natural regen. L. perenne Grass and flower Hedge SED (48df) a

0.00 0.00 0.00 0.00 0.00 0.00 0.00

a a a a a a

0.55 0.78 0.89 0.83 0.80 0.86 0.14

a ab b ab ab b

0.00 0.00 0.00 0.00 0.00 0.28 0.06

a a a a a b

0.07 0.00 0.13 0.15 0.20 0.86 0.12

a a a a a b

0.14 0.00 0.12 0.05 0.23 0.39 0.08

ab a ab a bc c

Same letter denotes no significant difference at the 5% level, by LSD multiple range test within fields and taxonomic group only.

Significant differences between sites were calculated with an LSD Multiple Range Test at the 5% level. The means, standard errors of difference and significant differences are given in Table 9.5. In Field 47, Hemiptera and adult Diptera were not found in any sample. There were no significant differences between the field and the field margin cereal plots for any group. Most groups were found in significantly higher numbers in the hedgerow than elsewhere, but no consistent pattern of abundance could be discerned among the grass and natural regeneration plots. However, there was an underlying trend of greatest numbers in the hedgerow, fewer in the mixed grass and wildflower and natural regeneration plots, with the least in the cereal margin plots and field samples. The data show that sown margins were used as overwintering habitat by a number of taxa within 12 months of establishment. Spatial Behavior of Ground Beetles Data collected using dry pitfall traps and mark-recapture techniques were analyzed over the sampling period to assess patterns of occurrence. Markedly different

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Summer

Autumn

110 100 90 80 70 60 50 40 30 20 10 0 0

10 20 30 40 50 60

0

0

6

12

18

24

30

10 20 30 40 50

0

10 20 30 40 50 60

Nebria brevicollis

Nebria brevicollis 0

6

12

18

24

30

Harpalus rufipes 0

4

8

12 16 20 24

110 100 90 80 70 60 50 40 30 20 10 0

0 10 20 30 40 50 60

Agonum dorsale 0

Figure 9.5

4

8

12

0

10 20 30 40 50 60

Pterostichus melanarius 0 10 20 30 40 50

0 10 20 30 40 50 60

Pterostichus cupreus 0

6

12 18 24 30

Cumulative trapping densities of different Carabidae in a hedge and in two adjacent arable fields over summer and autumn. (After Thomas et al., 2001.)

spatial behavior was apparent (Thomas and Marshall, 1999; Fernandez Garcia et al., 2000; Thomas et al., 2001) See Figure 9.5. Clearly, certain species were associated with the hedge, notably Harpalus rufipes. Others, such as Pterostichus cupreus, are found within the fields rather than the margins. Nebria brevicollis has an aestivation period, when it is limited to the field

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margin and hedgerow. In September, the adults move into the adjacent fields, where they may be involved in predation of crop pests active at this time of year (Fernandez Garcia et al., 2000; Thomas et al., 2001). This species requires different habitats at different times of year. Factors Affecting Flora Diversity in Field Margin Systems in European Landscapes Landscape Scale Studies Detailed analyses of the margin flora in contrasted landscapes in the three countries indicate that within areas, margin structure, particularly the upper vegetation layers, are major determinants of plant communities (Le Coeur, 1996; Le Coeur et al., 1997). In addition, adjacent land use and to a limited extent management are also factors that affect vegetation composition. Aspect, the orientation of the margin, appears to be unimportant. Analyses of three areas in France together separated sites on a spatial basis, indicating that (1) landscape structure is having an important effect of botanical composition and (2) disturbance and eutrophication (management and adjacent agriculture) also influence communities (Le Coeur et al., 1997). In the Netherlands, the plant communities in two areas were relatively species-poor, even where fields are small and margin density is high. This may reflect the intensity of agriculture. Within the U.K., the boundary communities within a polder landscape differ from a hedgerow area (Marshall et al., 1996). However, within the hedgerows, the flora are similar. Results comparing sites in the three countries were presented by (Le Coeur, 1996). Data from four areas are briefly considered below. Cossington, Somerset, U.K. — The permanent pasture throughout this area was dissected by land drainage channels with standing water present through the summer. In addition, slightly higher areas had hedges with one long shelterbelt present across the area. Correspondence analysis of the sites gave little separation, with the first two axes explaining only 14% of the variation within the data. Species ordinations on Axis 2 indicated a continuum from wetland (negative scores), through grassland to disturbed areas (positive scores). Principal component analysis (PCA), in contrast, ordinated those areas with hedges away from the wetter margins. The discriminating species with high component scores on Axis 2 included Crataegus monogyna, Rosa canina, and Hedera helix. Species with low scores included Juncus effusus, Carex riparia, Rumex acetosa, and Cerastium fontanum. The first two axes accounted for 30% of the variation in the data (23.8% and 7.1%), though the environmental or structural variables associated with Axis 1 are not clear. Corsham, U.K. — Reciprocal averaging correspondence analysis of the field margin ground-layer vegetation indicated that the majority of margins within the study area had similar flora. The ordination showed little grouping of sites, with the first axes accounting for only 14% of the variation within the data. The species with positive loadings on Axis 1 were typical of disturbed and arable habitats, while species with negative loadings were more typical of grassland and less-disturbed communities, indicating some effects of field management on the margin flora. The data, comprising

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85 sections, were subjected to TWINSPAN analysis (Marshall et al., 1996). The sites were divided into four groups. Tabulation of the structure of each margin, adjacent land use and management did not indicate major associations, reflecting the similarity of margins in the area. Nevertheless, the separations contain a spatial element in that one group consists of 19 sites, all located to the north of a road through the study area. One group is of 9 sites along the road verges, while the other two groups are mostly to the south of the road. These data indicate that some dissimilarity in plant communities results from location in the landscape. Linear elements such as roads and water courses may thus isolate habitats (Vanruremonde and Kalkhoven, 1991). Pleine-Fougères bocage — The bocage area of Pleine-Fougères is a mixed agricultural area with hedgerows, woodlots and fields of grassland with some maize and cereals. Correspondence analysis identified eight vegetation groups with a range of characteristic plant species. The results are summarized in Figure 9.6, as a classification of the margins and shows the structure of the margin as an important discriminator. Vegetation groups vary from dense hedges, to open hedgerows and to herbaceous strips that are open to disturbance. Mont Saint Michel bay polder — The polder is a flat area reclaimed in the 1800s from the Mont Saint Michel bay. The landscape is flat, dissected by dikes, with fields of maize, wheat and vegetables. The margins are usually wet or dry ditches or grassy strips. Analyses of the vegetation of the margins indicated that again the structure of the margin was an important discriminator, though the intensity of farming and management also influenced the flora (Figure 9.7). Herbaceous Plant Diversity on Two Farms, with and without Sown Grass Strips, in Wiltshire, U.K. A total of 94 higher plant species were found in the 117 relevées of the herb layer of hedge bottoms (Moonen and Marshall, 2001). Three species were restricted to Noland’s Farm and 24 species were found only on the Manor Farm, all of which had low frequencies. These data indicate that the two farms shared the same species pool. Following RDA analysis, the list of 14 variables, explaining 26% of the total variation in hedge-bottom vegetation, was retained for PCA. Of the 26%, management explains 12%, adjacent features 8%, and boundary structure 6%. Gapped-up hedges (18 relevées) contribute strongly to the diversity in hedge-bottom vegetation, and so do wide boundaries and boundaries with a sown grass strip. Coppiced hedges explain only 1% of the variation in the data set. However, gapping-up and coppicing hedges interact significantly which means that both explain similar variation, and gapping-up and coppicing are both important factors. After fitting the gapped-up hedges to the model, coppiced hedges explain a significant (P > 0.05) additional 1% of the variation. PCA with the 14 explanatory variables as passive variables resulted in three clearly distinguishable groups of hedges in the ordination diagram (Figure 9.8): the hedges on Noland’s Farm, the low hedges on the Manor Farm, and the gapped-up and coppiced hedges on the Manor Farm. Hedges on Noland’s Farm are characterized by Anisantha sterilis, Poa trivialis, Urtica dioica, Galium aparine, and Geranium dissectum. The Manor Farm hedges are characterized by Festuca rubra, Elytrigia

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Classification of field margins in the bocage. (From Moonen, 1995. With permission.)

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Figure 9.6

236

Figure 9.7

Classification of field margins in the bocage. (From Moonen, 1995. With permission.)

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FIELD BOUNDARY HABITATS 237

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Axis 2

238

Noland's Farm Manor Farm Coppiced hedges

Poa triv Holclana

Bromster Urtidioi Geradiss

Dactglom Cirsvulg Rubufrut Axis 1 Bracsylv Holcmol l Hedeheli

Anthsylv

Festrubr

Axis 2

Elymrepe

Noland's Farm Manor Farm Coppiced hedges

Dominant height Gapping-up Tree cover Shrub cover Woodlot Coppicing Mown Permeability of hedge Axis 1 Dirt road Width uncult. zone No shrubs in ditch Bank height Sown strip

Low hedge

Figure 9.8

Ordination diagram of first two PCA axes with 117 hedge-bottom samples: (a) position of 17 characteristic species: Anthsylv = Anthriscus sylvestris, Bracsylv = Brachypodium sylvaticum, Bromster = Anisantha sterilis, Cirsarve = Cirsium arvense, Cirsvulg = Cirsium vulgare, Dactglom = Dactylis glomerata, Elymrepe = Elytrigia repens, Festrubr = Festuca rubra, Galiapar = Galium aparine, Geradiss = Geranium dissectum, Hedeheli = Hedera helix, Holclana = Holcus lanatus, Holcmoll = Holcus mollis, Lolimult = Lolium multiflorum, Poatriv = Poa trivialis, Rubufrut = Rubus fruticosus, Urtidioi = Urtica dioica, (b) position on ordination axes of 14 explanatory variables (retained from RDA with forward selection and associated Monte-Carlo permutation test) that add significantly (P < 0.05) to the explanation of the species variation. (From Moonen and Marshall, 2001. With permission.)

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repens, Hedera helix, Brachypodium sylvaticum, Holcus mollis, and Cirsium vulgare. The coppiced and gapped-up hedges on the Manor Farm are characterized by Holcus lanatus and to a lesser extent by Silene dioica, which occurs in a very high percentage of these samples. Analysis of variance of the number of herbaceous species per 25-m hedge-bottom length between the hedges on Noland’s Farm, the low hedges on the Manor Farm, and the coppiced and gapped-up hedges on the Manor Farm, showed that all three groups differ significantly (P < 0.001) in species richness. The coppiced and gappedup hedges had the most species (23.2; sed = 1.36), followed by the other hedges on the Manor Farm (17.4) and hedges on Noland’s Farm (14.6). Stepwise linear regression of species richness and the 14 explanatory variables show that species richness in the hedge bottom is significantly (P < 0.05) increased by gapping-up of hedges. Also, the vegetation in the hedge bottom side directly next to a dirt road or sown strip had increased species richness. Overall, management of the Manor Farm hedges gives greater botanical diversity, indicating the grass strips reduce disturbance and enhance species richness.

DISCUSSION Field Margins in European Landscapes Studies of the flora and fauna of field margins in a range of European countries, farming systems and landscapes demonstrated that a range of factors are important in influencing the abundance and diversity of species (Burel et al., 1998). Consistently, the structure of the margins is important. Margins can contain a range of structural components and therefore a range of species and communities associated with them. Field utilization (cropping) is important, and farm type affects field margins. Farmers are particularly important in affecting margins, via their perceptions and requirements for farming and, thus management. The level of disturbance associated with adjacent farming and management also have profound influences. High disturbance, by both physical and chemical means, can reduce abundance and diversity of species (Kleijn and Snoeijing, 1997; Kleijn and Verbeek, 2000; Tsiouris and Marshall, 1998, Paoletti, 1999). The location of margins within the landscape is also influential (Le Coeur et al., 1997), mediating the opportunities for species dispersal and thus colonization and recolonization of habitats. Hedges connected to woodland are more likely to support woodland species, but other elements, such as roads, may isolate habitats. Effects of flora and fauna are found at both site and landscape levels. There is a general trend for a reduction in diversity and abundance with increasing landscape simplification and increasing disturbance via farm inputs, cultivation and management. There are also changes in the species compositions of field margins along such gradients. However, these changes are not simple or linear, and simple generalizations do not apply to all species within groups of both fauna and flora. Further, certain groups and species react to landscape at different scales. Thus, the implementation

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of general management prescriptions, e.g., for set-aside, should take account of scale effects as appropriate for the groups under consideration. A field survey of two farms, one with sown grass strips and one without, showed that introduced margins at arable field edges, together with accurate fertilizer application, could result in less disturbance in the field margin and increase botanical diversity. The technique of introducing field margin vegetation strips thus can increase biodiversity on farms. Processes Affecting Field Margins Small-scale experimentation shows that plants are affected by addition of fertilizer and herbicide and by management, including cutting. Fertilizer additions favor the establishment and growth of tall plant species, typically those with a ruderal habit (Marrs, 1993). Such species, including perennials, can colonize margin habitats early on in secondary succession and may dominate the community. In the crop edge, fertilizer effects on the arable flora are modified via the canopy and the light climate. Fertilizer promotes poorer light under the canopy, by favoring the taller crop. Detailed studies of the flora of the field boundary show that plants at the edge, within 20 cm of the tilled soil, are able to exploit the fertility of the crop, producing significantly more biomass than plants further into the margin (Kleijn, 1996). Thus, nutrients are “harvested” from the field into the boundary. This situation favors taller species while low-growing species are reduced (Kleijn, 1997). Further into the margin, reduced fertility allows greater species diversity. The effects of herbicides on plants are less predictable, partly as there are many chemicals with varying spectra of activity. Some herbicides have direct impacts on species, while others cause changes in plant communities indirectly, by allowing unaffected species to increase. In general, herbicide application or drift from field operations has negative effects on botanical diversity. Management, in the form of vegetation cutting, can also have impacts on the flora of field margins. Cutting and removal, as in hay harvesting, can remove nutrients and ameliorate the adverse effects of fertilizer additions. The inter-plant interactions that occur in field margins have been successfully modeled, using a range of species with differing life-history strategies (Schippers et al., 1999). The model builds on studies made within the project on establishment, competition and fate of plants, so that patterns of successional change in field margins are simulated. The model includes effects of fertilizer, herbicide, and cutting. Clearly, fertilizer additions lead to loss of subordinate species. Herbicides cause species loss and reduced diversity. Vegetation removal by cutting modifies competition and mortality, allowing species and therefore diversity to be maintained. Introducing Vegetation Strips at Field Edges Sown margin strips have been successfully established in a variety of situations in five European countries (Marshall, 1997). These strips have compared, under experimental conditions, sowing perennial grasses, grasses and wildflowers, wildflowers and naturally regenerating flora, with the field crop. Sown strips show

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successional changes, typically with annual weed plant species common in the first year which largely disappear in the second and subsequent years after sowing, except on regeneration plots. Successional patterns were similar between sites, indicating that soil fertility was a poor predictor of outcome. In general, few plants of the preexisting margin colonize the new strips. The sown strips showed some convergence toward grass margins with colonization by more mobile species of grassland. In general, the species present showed low dispersal capabilities (Marshall and Moonen, 1997) and seedbanks were often impoverished. Colonisation by species not previously recorded in the above-ground flora was very low, indicating that the use of seed mixtures is likely to be essential in most farm situations. The sown plots significantly reduced weed species populations. This effect was particularly apparent where the perennial Cirsium arvense achieved high populations where grasses were not sown in strips. The productivity of the strips was lower than might be expected on land taken out of arable production. Nevertheless, fertilizer use in the adjacent field affected plant growth, increasing biomass in the 10 to 20 cm nearest the crop (Kleijn, 1996). With the exception of some spread of the sown grasses, there was little evidence of the sown strips themselves causing weed problems in the adjacent crop (Marshall and Moonen, 1997; Smith et al., 1999; West et al., 1997). In a survey of margins on two farms, it was shown that sown grass margins were associated with less disturbed and more species-rich field margin flora, indicating that such strips would give some protection to the pre-existing margin flora, with farming operations taking place further from the margins (Moonen and Marshall, 2001). Invertebrates of Field Edges Field margins were shown to increase the diversity and abundance of insects, especially if they were both botanically and structurally diverse (Thomas and Marshall, 1999). In experiments using pitfall trapping, a technique that measures activitydensity, no significant differences were found between different field margin strips. However, it was demonstrated that the technique is unsuitable for comparing different vegetation structures and is unsuitable for small plots. Many invertebrates move significant distances, and studies should be made at the field scale, rather than the plot scale (Thomas et al., 1998). Alternative sampling methods showed that the more structurally complex and botanically rich plots supported the most abundance and diversity of invertebrates. A novel field technique of marking individual ground beetles was developed in order to study the dispersal characteristics of these invertebrates (Thomas, 1995). These species are often polyphagous predators, implicated in the control of aphid and slug pest populations. Many species were particularly mobile, moving from the field margin into the crop over short intervals. Introduced field margin strips were rapidly colonized, so that overwintering populations were similar to pre-existing margin habitat within 12 to 14 months of establishment (Thomas et al., 1994). Markrecapture techniques were deployed with pitfall trapping to assess total population size and dispersal characteristics of species. Behavior of species varied considerably. Some species were ubiquitous, while others were dependent on field margins for overwintering sites. One species used margins during a summer aestivation period,

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before dispersing into the crop in late summer/early autumn. Other species were part of a diverse community found within the arable crops. Mark-recapture studies provided quantitative results on dispersal for use in subsequent modeling, for example, maximum (c. 100 m day–1) and average daily displacement. Other significant findings were that patterns of occurrence were not uniform. Some species were found in consistently high densities in certain locations, the reasons for which are unknown but which might be manipulated to reduce pest populations (Thomas et al., 2001). Another finding was that field margins, particularly a hedge, may act as a barrier to dispersal between fields. Studies in Germany using mark-recapture methods demonstrated that ground beetles will move into adjacent crops in spring. A significant local influence of the field margin was recorded in the crop on populations of aphids. The reduction of aphids up to 5 m or more from the margin is likely to have resulted from a complex of predator species associated with the margin (Marshall, 1997). The results demonstrate that field margins can support a diverse invertebrate fauna, some of which can contribute to the agricultural control of pest species. Suitable manipulation of the field margin may enhance the diversity and abundance of insects. Managing Field Margins Disturbance, particularly in the form of fertilizer and herbicide contamination, has adverse effects on the diversity of the perennial flora of field margins. Data indicates that significant herbicide drift will occur over 3 m from the crop and up to 4 m for fertilizer applied by spinning disk machinery (Rew et al., 1992; Tsiouris and Marshall, 1998). Sown margin strips 3 to 4 m wide, extending pre-existing boundaries, have the capability of reducing such disturbance by buffering drift. Such strips would be best managed by cutting and removal of clippings at a time of year when ground-nesting birds would be least disturbed. In areas with a history of intensive agrochemical use, it is likely that the existing flora of field margins has adapted to high fertility conditions and is species-poor and unlikely to recover significant diversity without species introductions. Sown grass and wildflower strips would be suitable under such conditions. The seed used may need to be of local provenance. Sown perennial vegetation strips located at field edges would not be suitable for the encouragement of rare arable weed species, many of which are threatened with extinction in modern arable farming. Such species are often found in soil seed banks at field edges. Where such species are known to exist, the technique of no-input crop edges (conservation headlands, ackerrandstreifen) is suitable. Studies indicate no significant increase in pest and disease problems and minor increases in weeds under some conditions and on some soils. Studies on some species show that fertilizer in the crop has a significant adverse effect on rare weeds, mediated by a poorer light climate created by a competitive crop. Fertilizer should also be omitted from noinput crop edges for rare weed conservation (Kleijn and Van der Voort, 1997).

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CONCLUSIONS At the plot scale, field margin floras are affected by adjacent management. Plants of the margin can forage into the arable area over short distances. Sowing seed mixtures of grasses and flowers as a field margin strip is a practical means of increasing local diversity and can protect adjacent pre-existing boundary flora. There is evidence that the technique can reduce the abundance of competitive annual hedgerow weeds, while increasing available habitat for invertebrates. There is evidence of limited seed spread from sown margins into crop areas, but this is not likely to be of economic significance. At the field scale, impacts of field operations, particularly fertilizer application, are likely to be important for field margin flora. Contrasting results were shown in the development of margin flora: in sown strips, there was little evidence of farming system effect on the flora; in contrast, a farm with grass margins had significantly more diverse herbaceous hedge flora, compared with an adjacent farm without strips. Fauna studies show that species-specific spatio-temporal behavior occurs in Coleoptera. Margins are important as overwintering or aestivation sites. They may also be barriers to movement between fields for some species, which may have implications for recolonization and population recovery after field operations. Invertebrate abundance and diversity is encouraged by structural complexity and botanical diversity in margins. At the landscape scale, boundary structure, land-use (farming type), location and the management of the boundary affect the shrub and herbaceous flora. Disturbance and eutrophication from adjacent farming are important in affecting margins. These various factors are in fact a result of many specific environmental and physical processes, which require further understanding. However, it is clear that local diversity of structure and land use favor diversity in margins. With a diversity of land use in Europe, and a range of overlying climatic differences, margins are variable features of agricultural landscapes. In those landscapes examined, field margins are an important contributor to biological diversity, but they are sensitive to the farming operations practiced.

RECOMMENDATIONS 1. Sown margin strips at least 3 m wide should be introduced at arable field edges, to buffer the effects of fertilizer and pesticide drift and to create new habitat on farmland. The technique will make significant contributions to the maintenance of biological diversity in agricultural systems. 2. The structural diversity of field margins should be maintained at farm, field and landscape scales. 3. Implementation of agri-environmental measures, changes to farming support, and landscape planning should take account of their effects at the appropriate scales for different fauna and flora.

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ACKNOWLEDGMENTS This project was funded by the European Commission, contract AIR3 CT920476. We are grateful to the many researchers involved with the work, including Peter Schippers, Addi Kopp, Claudine Thenail, and many more. We are also grateful for associated funding from individual Member States that enhanced the overall program.

REFERENCES Barr, C., Howard, D., Bunce, R., Gillespie, M., and Hallam, C. (1991) Changes in hedgerows in Britain between 1984 and 1990. Institute of Terrestrial Ecology. Barr, C.J., Bunce, R.G.H., Clarke, R.T., Fuller, R.M., Furse, M.T., Gillespie, M.K., Groom, G.B., Hallam, C.J., Hornung, M., Howard, D.C., and Ness, M.J. (1993) Countryside Survey 1990. Main Report. Department of the Environment. Baudry, J. (1988) Hedgerows and hedgerow networks as wildlife habitat in agricultural landscapes. In Environmental Management in Agriculture. European Perspectives. (Ed. J.R. Park), 111–124. Belhaven Press, London. Burel, F. (1989) Landscape structure effects on carabid beetles spatial patterns in western France. Landscape Ecol., 2, 215–226. Burel, F. (1996) Hedgerows and their role in agricultural landscapes. Critical Rev. in Plant Sci., 15, 169–190. Burel, F. and Baudry, J. (1990) Hedgerow network patterns and processes in France. In Changing Landscapes: An Ecological Perspective (Eds. I.S. Zonneveld and R.T.T. Forman), 99–120. Springer-Verlag, New York. Burel, F., Baudry, J., Butet, A., Clergeau, P., Delettre, Y., Le Coeur, D., Dubs, F., Morvan, N., Paillet, G., Petit, S., Thenail, C., Brunel, E., and Lefeuvre, J.-C. (1998) Comparative biodiversity along a gradient of agricultural landscapes. Acta Oecologia, 19, 47–60. Denis, D., Thenail, C., Petit, S., Morvan, N., Moonen, N., Mérot, P., Le Coeur, D., Dubs, F., Burel, F., and Baudry, J. (1995) A method for analyzing field boundaries: Computerized management data. INRA-SAD Armorique, CNRS, URA ECOBIO, Rennes. Fernandez Garcia, A., Griffiths, G.J.K. and Thomas, C.F.G. (2000) Density, distribution and dispersal of the carabid beetle Nebria brevicollis in two adjacent cereal fields. Ann. Appl. Biol., 137, 89–97. Fuller, R.J., Gregory, R.D., Gibbons, D.W., Marchant, J.H., Wilson, J.D., Baillie, S.R., and Carter, N. (1995) Population declines and range contractions among farmland birds in Britain. Conserv. Biol., 9, 1425–1441. Gerowitt, B. and Wildenhayn, M. (1997) Ecological and economic effects of intensifying arable farming systems: Results of the Göttingen INTEX-project 1990–94. Forschungs- und Studientzentrum Landwirtschaft und Umwelt de Universität Göttingen, Göttingen. Greaves, M.P. and Marshall, E.J.P. (1987) Field margins: definitions and statistics. In Field Margins (Eds. J.M. Way and P.J. Greig-Smith), Vol. Monograph No. 35, 3–10. British Crop Protection Council, Farnham, U.K. Green, R.E., Osborne, P.E., and Sears, E.J. (1994) The distribution of passerine birds in hedgerows during the breeding season in relation to characteristics of the hedgerow and adjacent farmland. J. Ecol., 31, 677–692.

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Haines-Young, R.H., Barr, C.J., Black, H.I.J., Briggs, D.J., Bunce, R.G.H., Clarke, R.T., Cooper, A., Dawson, F.H., Firbank, L.G., Fuller, R.M., Furse, M.T., Gillespie, M.K., Hill, R., Hornung, M., Howard, D.C., McCann, T., Morecroft, M.D., Petit, S., Sier, A.R.J., Smart, S.M., Smith, G.M., Stott, A.P., Stuart, R.C., and Watkins, J.W. (2000) Accounting for Nature: Assessing Habitats in the U.K. Countryside, DETR, London. INRA (1976) Les Bocages: histoire, écologie, economie. In Compte Rendu de la Table Ronde CNRS “Aspects physiques, biologiques et humaines des écosystemes bocagers des régions tempérées humides” INRA, CNRS-ENSA et Université de Rennes. Jongman, R.H.G., Ter Braak, C.J.F., and Van Tongeren, O.F.R., Eds. (1995) Data Analysis in Community and Landscape Ecology, Cambridge University Press, Cambridge. 324 pp. Jörg, E., Ed. (1994) Field Margin-Strip Programmes. Landesanstalt für Pflanzenbau und Pflanzenschutz, Mainz. 182 pp. Kleijn, D. (1996) The use of nutrient resources from arable fields by plants in field boundaries. J. Appl. Ecol., 33, 1433–1440. Kleijn, D. (1997) Species richness and weed abundance in the vegetation of arable field boundaries. Ph.D. thesis, Agricultural University, Wageningen. Kleijn, D., Joenje, W., Le Coeur, D., and Marshall, E.J.P. (1998) Similarities in vegetation development of newly established herbaceous strips along contrasted European field boundaries. Agric. Ecosys. Environ., 68, 13–26. Kleijn, D. and Snoeijing, G.I.J. (1997) Field boundary vegetation and the effects of agrochemical drift: botanical change caused by low levels of herbicide and fertilizer. J. Appl. Ecol., 34, 1413–1425. Kleijn, D. and Van der Voort, L.A.C. (1997) Conservation headlands for rare arable weeds: the effects of fertilizer application and light penetration on plant growth. Biol. Conserv., 81, 57–67. Kleijn, D. and Verbeek, M. (2000) Factors affecting the species composition of arable field boundary vegetation. J. Appl. Ecol., 37, 256–266. Le Coeur, D. (1996) La végégetation des élements linéaires non cultivés des paysages agricoles: identification à plusieurs échelles spatiales, des facteurs de la richesse et de la composition floristiques des peuplements. Ph.D. thesis, Université de Rennes I, Rennes. Le Coeur, D., Baudry, J., and Burel, F. (1997) Field margins plant assemblages: variation partitioning between local and landscape factors. Landscape and Urban Planning, 37, 57–71. Marrs, R.H. (1993) Soil fertility and nature conservation in Europe: theoretical considerations and practical management solutions. Adv. Ecol. Res., 24, 241–300. Marshall, E.J.P. (1988) The ecology and management of field margin floras in England. Outlook on Agric., 17, 178–182. Marshall, E.J.P. (1989) Distribution patterns of plants associated with arable field edges. J. Appl. Ecol., 26, 247–257. Marshall, E.J.P. (1993) Exploiting seminatural habitats as part of good agricultural practice. In Scientific Basis for Codes of Good Agricultural Practice. Eur 14957. (Ed. V.W.L. Jordan), 95–100. Commission for the European Communities, Luxembourg. Marshall, E.J.P., Ed. (1997) Field Boundary Habitats for Wildlife, Crop and Environmental Protection. Final Project report of Contract AIR3-CT920476. Commission of the European Communities. 313 pp. IACR-Long Ashton Research Station, Bristol. Marshall, E.J.P., Baudry, J., Moonen, C., Fevre, E., and Thomas, C.F.G. (1996) Factors affecting the floral diversity in European field margin networks. In The Spatial Dynamics of Biodiversity. (Eds. I. Simpson and P. Dennis) 97–104. IALE(U.K.), University of Stirling.

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Marshall, E.J.P. and Moonen, C. (1997) Patterns of plant colonization in extended field margin strips and their implications for nature conservation. In Species Dispersal and Land Use Processes (Eds. A. Cooper and J. Power), 221–228. IALE(U.K.), Coleraine. Marshall, E.J.P. and Nowakowski, M. (1991) The use of herbicides in the creation of a herbrich field margin. In 1991 Brighton Crop Protection Conference — Weeds, 655–660. British Crop Protection Council, Farnham, U.K. Marshall, E.J.P. and Smith, B.D. (1987) Field margin flora and fauna: interaction with agriculture. In Field Margins (Eds. J.M. Way and P.J. Greig-Smith), 23–33. British Crop Protection Council, Farnham, U.K. Marshall, E.J.P., West, T.M., and Moonen, A.C. (1998) Creating and managing perennial field margin strips for botanical diversity in farmland. Gibier Faune Sauvage/Game and Wildlife, 15, 87–97. Moonen, A.C. and Marshall, E.J.P. (2001) The influence of sown margin strips, management and boundary structure on herbaceous field margin vegetation in two neighbouring farms in southern England. Agric, Ecosys. Environ. 86, 187–202. Moonen, C. (1995) The factors influencing field margin vegetation in two contrasted agricultural landscapes: bocage and polder. M.Sc. thesis, Agricultural University, Wageningen. Morris, M.G. and Webb, N.R. (1987) The importance of field margins for the conservation of insects. In Field Margins. BCPC Monograph No. 35 (Eds. J.M. Way and P.W. Greig-Smith), 53–65. British Crop Protection Council, Farnham, U.K. Paoletti M.G. (1999) Using bioindicators based on biodiversity to assess landscape sustainability. Agric. Ecosys. Environ., 74, 1–18. Paoletti M.G. (2001) Biodiversity in agroecosystems and bioindicators of environmental health. In Structure and Function in Agroecosystems Design and Management — Advances in Agroecology (Eds. M. Shiyomi and H. Koizumi), 11–44. CRC Press, Boca Raton, FL. Paoletti M.G. and Lorenzoni, G.G. (1989) Agroecology patterns in northeastern Italy. Agric. Ecosys. Environ., 27, 139–154. Parish, T., Lakhani, K.H., and Sparks, T.H. (1995) Modelling the relationship between bird population variables and hedgerow, and other field margin attributes. II. Abundance of individual species and of groups of species. J. Appl. Ecol., 32, 362–371. Pollard, E., Hooper, M.D., and Moore, N.W. (1974) Hedges. Collins, London. Rands, M.R.W. (1985) Pesticide use on cereals and the survival of grey partridge chicks: a field experiment. J. Appl. Ecol., 22, 49–54. Rew, L.J., Theaker, A.J., and Froud-Williams, R.J. (1992) Nitrogen fertilizer misplacement and field boundaries. In Aspects of Applied Biology — Nitrate and Farming Systems, Vol. 30, 203–206. Association of Applied Biologists, Wellesbourne, U.K. Schippers, P., Snoeijing, I., and Kropff, M. (1999) Competition under high and low nutrient levels among three grassland species occupying different positions in a successional sequence. New Phytologist, 143, 547–559. Schumacher, W. (1987) Measures taken to preserve arable weeds and their associated communities. In Field Margins. BCPC Monograph No. 35 (Eds. J.M. Way and P.W. GreigSmith), 109–112. British Crop Protection Council, Farnham, U.K. Smith, H., Firbank, L.G., and Macdonald, D.W. (1999) Uncropped edges of arable fields managed for biodiversity do not increase weed occurrence in adjacent crops. Biol. Conserv., 89, 107–111. Tansley, A.G. (1935) The use and abuse of vegetational concepts and terms. Ecology, 16, 284–307.

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ter Braak, C.J.F. (1987a) The analysis of vegetation-environment relationships by canonical correspondence analysis. Vegetatio, 69, 69–77. ter Braak, C.J.F. (1987b) CANOCO — a program for canonical community ordination. Microcomputer Power, Ithaca, New York. ter Braak, C.J.F. (1996) Unimodal models to relate species to environment DLO — Agricultural Mathematics Group, Wageningen. Thomas, C.F.G. (1995) A rapid method for handling and marking carabids in the field. Acta Jutlandica, 70, 57–59. Thomas, C.F.G., Cooke, H., Bauly, J., and Marshall, E.J.P. (1994) Invertebrate colonization of overwintering sites in different field boundary habitats. In Arable Farming under CAP Reform — Aspects of Applied Biology No. 40 (Eds. J. Clarke, A. Lane, A. Mitchell, M. Ramans and P. Ryan), 229–232. Association of Applied Biologists, Wellesbourne, U.K. Thomas, C.F.G. and Marshall, E.J.P. (1999) Arthropod abundance and diversity in differently vegetated margins of arable fields. Agric. Ecosystems and Environ., 72, 131–144. Thomas, C.F.G., Parkinson, L., Griffiths, G.J.K., Fernandez Garcia, A., and Marshall, E.J.P. (2001) Aggregation and temporal stability of carabid beetle distributions in field and hedgerow habitats. J. Appl. Ecol., 38, 100–109. Thomas, C.F.G., Parkinson, L., and Marshall, E.J.P. (1998) Isolating the components of activity-density for the carabid beetle Pterostichus melanarius in farmland. Oecologia, 116, 103–112. Tsiouris, S. and Marshall, E.J.P. (1998) Observations on patterns of granular fertilizer deposition beside hedges and its likely effects on the botanical composition of field margins. Ann. Appl. Biol., 132, 115–127. Vanruremonde, R.H.A.C. and Kalkhoven, J.T.R. (1991) Effects of woodlot isolation on the dispersion of plants with fleshy fruits. J. Vegetation Sci., 2, 377–384. West, T.M. and Marshall, E.J.P. (1996) Managing sown field margin strips on contrasted soil types in three Environmentally Sensitive Areas. In Aspects of Applied Biology (44) Vegetation Management in Forestry, Amenity and Conservation Areas, 269–276. Association of Applied Biologists, Wellesbourne, U.K. West, T.M. and Marshall, E.J.P. (1997) Establishment and management of grass and wild flower strips at arable field edges in environmentally sensitive areas. In Grassland Management in Environmentally Sensitive Areas. BGS Occasional Symposium No. 32 (Ed. R.D. Sheldrick), 290–292. British Grassland Society. West, T.M., Marshall, E.J.P., and Arnold, G.M. (1997) Can sown field boundary strips reduce the ingress of aggressive field margin weeds? In 1997 Brighton Crop Protection Conference — Weeds, 985–990. BCPC, Farnham, U.K. West, T.M., Marshall, E.J.P., Westbury, D.B., and Arnold, G.M. (1999) Vegetation development on sown and unsown field boundary strips established in three environmentally sensitive areas. In Aspects of Applied Biology (54): Field Margins and Buffer Zones: Ecology, Management and Policy, 257–262. AAB, Wellesbourne. Whelon, D. (1994) The Hedgerow Incentive Scheme. In Hedgerow Management and Nature Conservation (Eds. T.A. Watt and G.P. Buckley), 137–145. Wye College Press, Wye. Wilson, P.J. (1993) Conserving Britain’s cornfield flowers. In 1993 Brighton Crop Protection Conference — Weeds, Vol. 1, 411–416. British Crop Protection Council, Farnham, U.K. Wratten, S.D. (1988) The role of field boundaries as reservoirs of beneficial insects. In Environmental Management in Agriculture: European Perspectives (Ed. J.R. Park), 144–150. Belhaven Press, London.

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CHAPTER

10

Changes in Landscape Diversity Patterns in the Province of Wielkopolska, Poland, Influenced by Agriculture Andrzej Mizgajski

CONTENTS Introduction............................................................................................................249 Natural Landscape .................................................................................................250 Development of Agricultural Landscape...............................................................253 Present-Day Changes in Agricultural Landscape .................................................257 Conclusions............................................................................................................260 References..............................................................................................................261

INTRODUCTION Wielkopolska is a historical region situated on the Central European Plain, in the drainage of the Warta, a tributary of the Odra. The main relief features of the region are the result of Pleistocene glaciations that moved in from the north. Consequently, Wielkopolska’s landscape changes from the north to the south although it has no clear natural borders in the west and the east. In comparison to other regions of Poland, Wielkopolska has had a unique history that is reflected in its economic structure. This is especially true with regard to the last two centuries, when, because of the agricultural and industrial revolution, the modern economic structure of the region was taking shape. In the 19th century, the area roughly corresponding to historical Wielkopolska was a separate province under Prussian occupation. After Poland regained independence in 1918, the region continued as a compact administrative unit known as a voivodeship. Only between 1975 and 1998 was the region

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divided into smaller administrative units. Statistics quoted in this chapter refer to Wielkopolska within the historical administrative boundaries that existed at a given time. A characteristic feature of the economy of today’s Wielkopolska is highly intensive agriculture and a well-developed farm produce processing industry. The share of acreage of large farms (approximately 20%), in comparison to that of small peasant family holdings, is much higher here than in central Poland. Throughout the region’s history, agriculture exerted the strongest anthropogenic impact on ecosystems, which is reflected in the landscape. Man’s impact on the environment has severely reduced the percentage of the land that is a natural or semi-natural ecosystem. For example, nature reserves cover only 0.18% of the present-day voivodeship of Wielkopolska.

NATURAL LANDSCAPE The major natural characteristics of the region came into being during Pleistocene glaciations, which covered the area three times from 1 million to 11,000 years BP. They left behind a hilly, undulating, and plain terrain lying, for the most part, at 60 to 120 m above sea level. The lowest valley bottoms lie below this range, while end moraines rise above it. In terms of geological structure, boulder loams — a glacial sediment, and sands, both loamy and friable glacio-fluvial and fluvial sediments, in part reshaped by wind, dominate close to the surface. Medium-fertile and poor soils developed on them. The latest glaciation (Würm) engulfed the northern part of the region, dividing it into two parts with different landscapes. The northern part shows greater relief energy and has glacial channels, on the bottom of which are many lakes. The southern part was molded by earlier glacier transgressions and certain processes occurring in the forefront of the last continental ice-sheet. The terrain here is less varied due to denudation, and there are no natural water reservoirs. Wielkopolska lies in the temperate zone. Its weather is characterized by the influx of polar-maritime air masses from the west, which dominate in the warm months. In winter and spring, a considerable impact on the weather is exerted by arctic and polar-continental air masses coming from the north and east (Wos´ 1994). Average temperatures for July, the warmest month, are 17.5 to 18°C, while in January, the coldest month, the average temperature is –2 to –3°C. Maximum rainfall is observable in summer (approximately 40%), while in the remaining three seasons the amount of precipitation is rather uniform. On average, the region receives 500 to 600 mm of rainfall annually. There are two basic types of natural landscape: (1) the plain and undulating landscape of the lowlands and (2) the landscape of valleys and depressions (Figure 10.1). Within each type, there are several subtypes of peculiar morphogenetic character. A consequence of the different types of substratum development is the varied properties of the soil and relief which, in combination with the climate, are responsible for local peculiarities of vegetation. The original vegetation of Wielkopolska was forests (Wojterski et al. 1978, Wojterski et al. 1981). On relatively fertile soils of flat and undulating morainic

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Figure 10.1

251

Natural landscapes of Wielkopolska. Legend: Flat and undulating landscapes: 1 — glacifluvial, 2 — glacial, 3 — periglacial. Landscapes of hills and heights: 4 — glacial and glacifluvial. Landscapes of valleys and depressions: 5 — flood plains, 6 — higher fluvial terraces, 7 — swamp plains. Landscapes strongly transformed anthropogenically: 8 — compact urban and industrial developments, 9 — strip-mining of lignite. (Adapted from Kondracki 1997.)

plateaus, dry-ground forests developed, whereas on higher valley terraces and outwash deposits poor habitats of mixed and pine forests grew. Periodically flooded, the bottoms of river valleys were covered with riparian forests, while small, frequently peaty depressions with little or no runoff supported alder carrs. Original vegetation in individual landscape types is shown in Table 10.1. In the first phase of human history, man was an element of the structure of natural ecosystems. From the point of view of the flow of matter and energy, those were

Sands of fluvial terraces

Glacier tills, glacial sands Periglacial plains with boulders

Dolina Konin´ ska [Warta Valley by Konin]

Dzielnica Krotoszyn´ ska [District of Krotoszyn]

Source: Adapted from Trampler et al. 1990.

Outwash deposits

Sandry Gnie´znien´ skie [Outwash Plains of Gniezno]

Pino-Quercetum

Galio-Carpinetum

Fraxino-Alnetum

Galio-Carpinetum

Terraces with Leucobryo-Pinetum dunes, flood plains

Outwash, lake district

Glacier tills, morainic sands with boulders

Pojezierze Wielkopolskie [Wielko polskie Lake District ]

Flood plains, terraces with dunes Hilly, lake district

Peats, alluvial soils and fluvial sands

17%

31.9%

19.4%

17.3%

19.8%

41.3%

Leucobryo-Pinetum Pino-Quercetum

Terraces with dunes, outwash, lake district

43%

51.5%

Leucobryo-Pinetum Ficario-Ulmetum

Percentage of Forests

Terraces with Leucobryo-Pinetum dunes, flood plains

Flood plains, terraces with dunes

´ rodkowej Noteci Dolina S [Valley of the Middle-Notec´ ]

Outwash deposits, sands of fluvial terraces, alluvial soils and fluvial sands, eolian sands Sands of fluvial terraces, Równina Nowotomysko-Kargowska [Plain of Nowy Tomy´s l and Kargowa] alluvial soils and fluvial sands

Sands of fluvial terraces, alluvial soils and sands, peats

Dominant Natural Landscape Type

Pine 80.8% Oak 7.4% Beech 0.4% Alder 4.7% Pine 81.0% Oak 5.7% Alder 4.8% Pine 93.1% Oak 0.5% Alder 3.0% Pine 61.7% Oak 23.6% Beech 0.3% Alder 5.3%

Pine 92.8% Oak 2.0% Beech 0.5% Alder 2.2% Pine 93.6% Oak 1.1% Beech 0.3% Alder 1.5% Pine 88.1% Oak 3.6% Beech 0.6% Alder 4.0%

Prevailing Tree Species in Tree Stands

252

Puszcza Notecka [Wood of the Notec´ River]

Pradolina Warty [Pre-Valley of the Warta River]

Dominant Sediment Type

Dominant Associations of Potential Natural Vegetation

Potential Natural Vegetation and Forests of Wielkopolska by Natural Landscape Types

Subregional Natural-Geographical Units

Table 10.1

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self-regulating systems that were characterized by a long-term balance between the production of biomass and its conversion into energy (Pianka 1974). In those early days, similar to other organisms, man was totally dependent on the supply of food and on other environmental factors.

DEVELOPMENT OF AGRICULTURAL LANDSCAPE Agriculture is the form of human activity that has had a decisive impact on the landscape throughout history. The origins of agriculture are related to the Neolithic revolution, or the process of transforming societies of hunters and gatherers into semi-settled and settled societies of food producers. It is widely accepted that in Wielkopolska the process began over 6,000 years ago, when the agricultural landscape began to emerge and later expand at the expense of the natural landscape over the next centuries. The earliest cultivated areas appeared in well-watered places where soil was light and medium-cohesive, next to lakes and in river valleys, and connected to the regulation of ground water. According to Kurnatowski (1975), the share of the agricultural landscape did not exceed 10% in Wielkopolska in the 10th century. Later, settlement moved to higher areas, a tendency that became more conspicuous in the 13th century (DuninWa˛ sowicz 1974). The reason behind the move was a rapid growth of population and increased felling of forests, in particular, for constructing strongholds. Continued felling reduced the share of forests in Wielkopolska to 50 to 60% in the 14th century (H l ady l owicz 1932, B l aszyk 1976). The consequences of forest clearings included a change of river regimes and more frequent overflooding which, in turn, made it necessary to move settlements to higher ground, leaving valley bottoms to renaturalize slowly. Larger portions of the natural landscape survived on the bottoms of large river valleys until the late phase of the self-supportive economy. The retreat of settlements from river valley bottoms meant a forced change in, but not abandonment of, the cultivation of hydromorphic soils. An important role in the expansion of the agricultural landscape in wet areas was played by Cistercian monks, who arrived in Wielkopolska in the 12th to 13th centuries. The second phase of the expansion took place in the 17th and 18th centuries, when settlers from western Europe, mainly from Holland, came to Poland. Their settlements (in Polish ole˛dry) were established on wet wastelands that they subsequently cultivated. Cultivation works were most intensive in the last decades of the 18th century because of large-scale river regulations increasing the runoff rate. A peculiar trait of self-supporting economy was the multiple use made of individual kinds of farmland that are clearly kept separate today. Animals, for instance, were grazed not only on pastures but also on winter crops, in forests and on meadows. Agroecosystems also had forests as an element. They were a source of animal feed (acorns, mast, young tree shoots) and a grazing area. Intensive use of forests by selective tree felling and grazing degraded these ecosystems, resulting in their changing into heathland.

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A common trait of different agricultural systems throughout this period was a self-supporting type of economy. It was characterized by the absence of external, anthropogenic feeding of agroecosystems with matter and energy. The fertility of soils in self-supportive land cultivation systems was maintained by burning spontaneous vegetation (swidden farming), fertilizing with livestock excrements and natural regenerative processes (fallow farming) (Kostrowicki 1973). With growing population and developing farm produce market, the output of biomass from agroecosystems grew, while there was no external feeding with nutrients. In consequence, soil productivity fell, making it necessary to begin cultivating ever-newer land at the expense of the natural forest landscape. This process continued in Wielkopolska until the first decades of the 19th century, when farmlands reached their greatest acreage. According to different sources, in the early 19th century forests in Wielkopolska occupied as little as 20% of the land (Baur 1842, Janczak 1965). From 1801 to 1806, Meitzen (1868–1871) specified the structure of land use in what was then the Grand Duchy of Posen (an area roughly corresponding to Wielkopolska) in the following manner: meadows, pastures, used forested areas and wastelands made up 69.6%, 23% was taken up by arable land, and only 7.4% were covered by forests. It can be estimated that over half of the region’s area was taken up by extensively used elements of the agricultural landscape, including forest pastures and land lying fallow. In the 19th century, a new quality emerged in the human impact on the environment owing to the departure from the self-supportive economy and the growth of external feeding of agroecosystems with matter and energy. The main reasons were the introduction of artificial fertilizers and mechanical draught. The result was a stop to oligotrophication of agroecosystems and a more intensive land use. The main stimulus of the change in agriculture was the emancipation of peasants and a gradual drawing of them into the system of market economy. Wielkopolska was at that time within the borders of Prussia, where agrarian reforms were introduced in the 1820s and 1830s. Economic and ownership changes were reflected in the landscape by the shrinking of wastelands and the more intensive use of agricultural and forest ecosystems. In 1864, the share of wastelands in Wielkopolska was estimated at 16,500 ha (0.1% of the region) (Meitzen 1869–1871); however, among the very extensively used areas one has to consider lands classified as pastures (6% of the region). At the same time, the share of arable land reached 60%. However, it must be considered that some of this area lay fallow. Fallow farming was replaced by crop rotation in Wielkopolska in the course of the second part of the 19th century. This change was reflected in the landscape from which wastelands disappeared and were replaced by arable land, whose share increased by 25% (Klein 1973). Arable lands reached their greatest share in 1921 when they occupied two thirds of the region’s area. The reason behind this increase was the food shortages during World War I and immediately afterward. Another feature of the agricultural landscape is the size structure of individual holdings. In the 19th century, only 30% of farmland was taken up by small peasant holdings. Complexes of them made enclaves among huge estates of great landowners. Dramatic changes in the structure of individual holdings were brought about by parcellation, which affected the largest holdings in the period from Poland’s regaining

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of independence in 1918 until World War II. As a result, the proportions were reversed and the share of small peasant holdings exceeded two thirds. The size structure of individual holdings that ensued then has not changed much until this day. A peculiar trait of the evolution of Wielkopolska’s agricultural landscape over the last 200 years is the elimination of infertile sandy lands from cultivation and instead afforesting them. The forests only slightly contracted in the 19th century, but profound structural changes did occur in their distribution. In the wake of the Napoleonic Wars, Prussia suffered from a deep economic crisis. A shortage of capital made many owners cut down their forests. This practice was further encouraged by the development of industry and a growing demand for timber. At the same time, the government encouraged afforestation, which became particularly intensive in the latter half of the century. What was afforested were heathland and the poorest, sandy cropland; they were planted with fast-growing conifers, particularly pine. Since the 1920s, the percentage of arable land has been on the decline, while the share of forests has been growing. According to statistics, from 1921 to 1973 forested areas grew by almost 170,000 ha in the voivodeship of Wielkopolska making the percentage of forests rise from 18.1 to 23.5%. Later, however, the share of forests remained stable. Afforestations carried out in the period between the two world wars were primarily a consequence of a difficult situation in agriculture and unprofitability of farming on the least fertile soils. After World War II, a sizeable amount of afforestation was necessitated by errors in methods of farming on sandy soils belonging to state-owned or collective farms. In an effort to maximally increase crop yield at minimum outlays, it was a common practice to use large doses of fertilizers, in particular ones with nitrogen, and to abandon fertilizing with manure. Such a cultivation of light sandy soils led to a dramatic decline in organic content of soil and its rapid depletion. Consequently, afforestation was necessary to reclaim the soils. A good illustration of this process is the change in the landscape structure in the poviat, or county, of Mie˛ dzychód situated in the northwestern corner of Wielkopolska (Figure 10.2), where forested areas grew by as much as 60%. Such intensive afforestation was a result of the prevalence of poor soils in the poviat. Next to tree felling, changes in water relations are a major influence exerted by agriculture on the landscape. The present state of the landscape owes much to the regulations of the Odra, Warta, Notec´ , and Obra rivers, increasing the runoff rate. Vast regulation projects were undertaken in the last quarter of the 18th century making approximately 200,000 ha of valley bottom part of agroecosystems (Henning 1979, Falkowski and Kar l owska 1961). Betterment drainages of land were continued until modern times; their intensity has noticeably decreased only recently. The area where betterment drainages have been carried out exceeds 1 million ha, i.e., 55% of farmland, in the voivodeship of Wielkopolska. The disappearance of water mills, sawmills and fuller mills, the functioning of which required retention of water to drive the machines, also contributed to the dehydration of the landscape. It is estimated (Go l aski 1980) that in the late 18th century, in the lower Warta drainage alone, there were 420 such establishments; after only 150 years they were almost entirely gone.

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Figure 10.2

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Development of land-use structure in the poviat of Mie˛ dzychód since the 19th century. Legend: 1 — cereal crops, 2 — crops other than cereals, 3 — fallow land, 4 — meadows, 5 — pastures, 6 — forests, 7a — surface waters, 7b — developed areas, roads, 8 — heathland. (After Mizgajski 1990.)

Human activities aimed at increasing the rate of water runoff from ecosystems have led to profound, qualitative changes in the landscape of Wielkopolska (Kaniecki 1991). One such change is the lowering of subsurface water, by several dozen centimeters, to two meters. Another is the lowering of lake surfaces by 13% on the average, between 1890 and 1980, which is evident from cartographic analysis. However, the process was much more rapid in the case of small lakes (up to 20 ha), where the decline in surface area reached 50%. The smallest bodies of water (up to 1 ha) tended to disappear totally; from about 1890 to 1960, their numbers fell from over 11,000 to around 2,500. Because of drainages, the acreage of farmland has indeed grown, but problems related to the overdrying of land have appeared as well. Those problems become more acute with more intensive crop production. The landscape and ecological consequences of anthropogenic changes in water relations led to the hypothesis that Wielkopolska was “turning into a steppe” (Wodziczko, 1947) or, to use today’s terminology, that it is drying up. Successive studies revealed the following changes in ecosystems:

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• Hydrological parameters — lowering of low water marks and ground-water table • Soil properties — overdrying, gleying recession, and a quicker mineralization of organic substance causing a decrease in humus content • The vegetation cover — elimination of swamp and riparian forests, spread of xerophytes and plant associations typical of dry habitats • The fauna — decrease in the number of forest species in favor of species living in an open landscape; appearance of xerophilous mollusk species

The above list of consequences must be supplemented with a list of changes brought about by the elimination of surface waters, such as the disappearance of belts of spontaneous vegetation that serve as biogeochemical barriers deciding the buffer capacities of agroecosystems. (Ryszkowski 1999). An illustration of the extent to which this process took place in the second half of the 20th century may be the recorded changes in the landscape surrounding the village of Zamorze, located about 50 km west of Poznan´ (Mizgajski and Kafel-G l e˛ bowska 1990). In an area approximately 12 km2, about 50 point and linear changes of topographical landscape elements that occurred in 1940–1982 were recorded. The most frequent type of change (27 places) was the drying up of ponds, in part accompanied by burying or removing of spontaneous vegetation communities surrounding them. Twenty cases of drainage ditch burying were recorded, frequently accompanied by the elimination of tree and bush belts growing along them. Furthermore, trees were felled along abandoned roads or ploughed field margins (six cases). A clear majority of changes consisting of the elimination of small landscape elements were direct or indirect consequences of drainage works carried out mostly in the 1970s. In this respect, the example of the village of Zamorze can be treated as representative of the whole of Wielkopolska.

PRESENT-DAY CHANGES IN AGRICULTURAL LANDSCAPE Present-day intensive farming is characterized by extremely heavy inputs of matter and energy into agroecosystems by man. This is clearly seen in very high doses of artificial fertilizers. Moreover, the rise of large pig farms using industrial feeds resulted in breaking earlier systemic ties between crop and stock farming. Farmers ceased to rely on the supply of manure from their own animals for crop cultivation, replacing it with artificial fertilizers and catch crops. Owing to industrial feeds, the size of a stock farm ceased to be dependent on the amount of feed produced by the farm, i.e., on the acreage of cropland. Furthermore, farmers, who were earlier bound to their farms, which were the sources of subsistence, turned into workers supplying labor, while the farms ceased to be sources of produce for them. Thus, agroecosystems changed from closed systems dominated by stabilizing internal flows of matter and energy into open systems, where external relations are of primary importance (Mizgajski 1990). Any errors in controlling such systems lead to uncontrollable changes in the landscape. In Wielkopolska, these changes were observable primarily on large state farms that had a priority in the supply of means of production. In the 1970s and 1980s, the use of artificial fertilizers grew rapidly in such farms, accompanied by the rise

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of large animal herds. This increased the significance of agricultural nonpoint pollution leading to the eutrophication of ecosystems and landscape effects such as the disappearance of lakes. This process continues despite the fact that agriculture became less intensive in the 1990s. The change of the political system in Poland initiated the process of profound socio-economic changes in rural areas. Subjecting agriculture to market pressures and abolishing subsidies to great state-owned farms resulted in an overall decrease in the intensity of land use. Poland’s transition to a market economy consisted mainly of the release of prices, withdrawal of subsidies to businesses, and deregulation of foreign trade. As a consequence, the ratio between produce prices and those of manufactured goods became less and less advantageous. This, in turn, resulted in the lowering of agricultural production intensity due to the shortage of funds for basic means of production, including fertilizers and pesticides. In due course, the consumption of fertilizers in central Wielkopolska fell from over 250 kg NPK/ha in the 1980s to approximately 100 kg NPK/ha in the early 1990s. The intensity of fertilizer use began to climb again to approximately 130 kg NPK/ha in the late 1990s. Decreased use of fertilizers was not reflected, however, in less eutrophication pressure exerted by agriculture on the environment. Go l dyn and Grabia (1998) investigated the drainage of the Cybina, one of the smaller tributaries of the river Warta. They estimated that from the catchment area of 15,600 ha, the river annually receives almost 120 tons of N and over 5 tons of P as agricultural nonpoint pollution. From the point of view of matter flow, the landscape of Wielkopolska is dominated by autonomous areas (plains) with a significant share of allochthonous areas (no-drainage depressions). A smaller share is taken up by sloping areas, known as transit ones. As a result, the ecosystems of the region tend to retain substances introduced to them. Consequently, one should not expect that the decline in the use of fertilizers would be reflected soon in lower numbers of biogens in ecosystems. Thus, it can justifiably be claimed that present-day changes in Wielkopolska’s landscape consisting of the disappearance of lakes are largely caused by eutrophication brought about by agricultural nonpoint pollution. The landscape changes aggravate the consequences of earlier draining projects that induced irreversible changes in water conditions. The high price of the means of agricultural production and the low price of farm produce make farmers more interested in afforestation of the poorest lands. Such lands are usually found in large complexes, in areas that already now have a high percentage of forests. New afforestations will simplify the landscape by combining forested areas into large forest complexes, whereas good soils will be even more intensively farmed since their afforestation is practically out of the question for economic reasons. To counteract the simplification of the landscape-ecological structure of such areas, it is necessary to increase the share of biotopes of seminatural vegetation, specifically by planting trees along field margins and roads. Such actions have already been taken in Wielkopolska, and there are plans to continue them (Ryszkowski et al. 2000). An important factor influencing landscape appearance is the field structure. In Wielkopolska, family farms (a total of 150,000) dominate, occupying in aggregate almost 80% of farmland. Their average size is about 7 ha in

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the southern and eastern parts of the region and up to 15 ha in the northern part. Usually, land belonging to one farm is spread over several places, which means that individual fields are only a few hectares in size. Fields belonging to large farms, as a rule, make up compact complexes, with the size of individual fragments exceeding 100 ha. The present agrarian structure may not be considered stable. In the future, one can expect the concentration of land ownership and field size to grow. Such a trend poses a danger of eliminating spontaneous vegetation growing in uncultivated habitats, in particular trees and shrubs. Structural changes may also result in a temporary increase in the share of fallow land in the landscape. In many parts of Poland, vast tracts of less fertile land are already left to lie fallow. This is especially true for former large state-owned farms. Meanwhile, in Wielkopolska, such lands are only marginal and, as such, virtually cannot be seen in the landscape. An important aspect of the agricultural landscape is rural settlement. Its most common form is a compact village consisting of a dozen to several dozen homesteads. The spatial arrangement of homesteads varies depending on the age and origins of a settlement (Szulc 1972). In total, there are 3,746 rural settlement units in the voivodeship of Wielkopolska, which gives on average 5 km2 of farmland per one village. Few and far between are individual homesteads surrounded by fields. Such sites came into being as a result of the parcellation of great landed properties carried out at the turn of the 19th century and in the 1920s and 1930s. Another type of settlement is made up of granges with adjoining workers’ quarters. This type of building arrangement underwent the greatest transformations when farms were stateowned (1950–1990). It was then that many shabby farm buildings and farmhouses were built; poor quality workmanship and architecture and wasteful use of space characterize these constructions. In the 1990s peasant homesteads were adapted for recreational purposes. The major force behind this process was a low return on farming on mediocre lands, which are often found in recreationally attractive areas, near lakes, surrounded by forests and varied land relief. After their use is changed, such buildings stand out favorably against poor homesteads of farmers. In suburban areas, the process of urbanization of the agricultural landscape is rapidly gaining momentum. One consequence of this process is a change in the character of suburban villages, where fewer and fewer peasant homesteads are found, while residential housing is mushrooming, sometimes giving shelter to small businesses as well. In suburban areas, in particular along main roads, agricultural landscape is replaced by single-family housing estates or, in Poznan´ ’s vicinity, by industrial parks. One can also speak of the urbanization of rural areas in Wielkopolska in a qualitative sense because of the improving infrastructure in rural areas. The road network is getting more dense (presently over 80 km of roads with hard surface per 100 km2) and about 70% of homesteads have access to a water supply network. Unfortunately, the construction of sewage disposal networks lags behind, with only slightly more than 10% of farms connected to a sewage system. Admittedly, some sewage is brought to treatment plants in cesspool emptiers; however, it can be assumed that most of it is discharged to the ground and waters causing contamination.

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CONCLUSIONS The present-day landscape is a combination of natural features and tendencies and the human impact on the environment. Agriculture played the most important role in landscape transformation. Historically speaking, the agricultural impact on the landscape of Wielkopolska can be divided into three qualitatively different phases: • Domination of the process of expansion of the agricultural landscape at the expense of the natural one; this phase was related to self-supportive economic systems • Domination of qualitative changes in the agricultural landscape related to increased inputs of matter and energy to agroecosystems, beginning with the industrial-agricultural revolution of the 19th century • Decrease of the agricultural landscape due to afforestation and urbanization, processes that have become more intensive since the mid-20th century

The gradual expansion of the agricultural landscape continued until the beginning of the 19th century, bringing the area occupied by natural forest ecosystems to a minimum. Present-day forests are almost entirely the effects of plantings that are now in various phases of re-naturalization. Agriculture is also responsible for changes in the landscape that has been shaped earlier by farming. Examples of qualitative changes in the landscape induced by agriculture include: • Overdrying of landscape due to a quicker rate of river runoff, draining of land and elimination of small retention • Eutrophication of ecosystems as a result of the irrational use of artificial fertilizers and slurry leakage • Decline in biodiversity and landscape diversity because of the elimination of spontaneous vegetation from the agricultural landscape

For about 50 years, a tendency has been observed whereby the agriculture landscape has been shrinking in favor of forests and urban areas. These changes lead to the simplification of the landscape and diminishment of its diversity because of the increasingly greater share of forest complexes in areas of poor soil, more intensive farming in areas of fertile soil, and increasing urbanization in suburban areas. Further development of the agricultural landscape will be conditioned by economic and cultural factors as well as legal regulations. Today’s tendencies are related to the ever-closer integration of Poland with the European Union, and they make the agricultural landscape more contrastive. Agroecosystems based on fertile soils are subject to the increasing pressure of agriculture, while poor soils are taken out of crop or stock production and set aside for afforestation. Of vital importance for the future of the agricultural landscape and agriculture itself will be a change in the role of farmers. It is necessary to introduce such mechanisms that would make them not only food producers, paid according to the size of production, but also conservators of those fragments of nature that they jointly manage. Successfully implemented, such mechanisms will improve farm produce quality, decrease man’s pressure on ecosystems, and raise aesthetic values of the landscape.

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REFERENCES Baur K. F. 1842. Forststatistik der deutschen Bundesstaaten. Brockhaus, Leipzig. Teil I, 272 pp., Teil II, 280 pp. B l aszyk H. 1976. Zmiany lesistos´ ci Wielkopolski [Changes in Forest Cover of Wielkopolska]. Roczniki Akademii Rolniczej w Poznan´ iu, Poznan´ , 73, 1–47. Dunin–Wa˛ sowicz T. 1974. Zmiany w topografii osadnictwa Wielkich Dolin na Niz· u S´ rodkowoeuropejskim w XIII wieku [Changes in Topography of Settlement of Great Valleys on the Central European Plain in the 13th Century]. Zak l ad Narodowy Imienia Ossolin´ skich, PAN, Wroc l aw-Warszawa, 178 pp. Falkowski M., Kar l owska G. 1961. Rozwój l˛a karstwa w Wielkopolsce [Development of Meadow Cultivation in Wielkopolska]. Poznn´ skie Towarzystwo Przyjació l Nauk, Prace Komisji Nauk Les´ nych, IX, 2, Poznan´ , 198 pp. Geografia, 5, 1964, Zeszyty Naukowe Uniwersytetu im. Adama Mickiewicza w Poznn´ iu, Nr 52. Go l aski J. 1980, 1988. Atlas rozmieszczenia m l ynów wodnych w dorzeczach Warty, Brdy i cze˛´sci Baryczy w okresie 1790–1960 [Atlas of Water Mills in the Drainages of the Warta, Brda and Part the Barycz in 1790–1960]. Akademia Rolnicza, Poznan´ , Part 1, 107 pp., Part 2, 100 pp. Go l dyn R. and Grabia J. 1998. Program ochrony wód rzeki Cybiny [The Cybina River Protection Program]. Urza˛ d Miasta, Poznan´ , 101 pp. Henning F.-W. 1979. Landwirtschaft und ländliche Gesellschaft in Deutschland. Part 2, 1750–1976. Ferdynand Schönigh, Padeborn, 287 pp. H l ady l owicz K. 1932. Zmiany krajobrazu i rozwój osadnictwa w Wielkopolsce od XIV do XIX wieku [Changes in the Landscape and the Growth of Settlement in Wielkopolska from the 14th to the 19th c.]. Instytut Popierania Polskiej Twórczosci Naukowej Lwów, 256 pp. Janczak J. 1969. Okre˛ gi Rolnicze Polski Zachodniej i Pó l nocnej w Pierwszej Po l owie XIX Wieku [Agricultural Centers of Western and Northern Poland in the First Half of the 19th Century]. Zak l ad Narodowy Imienia Ossolin´ skich, PAN, Wroc l aw-WarszawaKrakówWroc l aw, 226 pp. Kaniecki A. 1991. Problem odwodnienia Niziny Wielkopolskiej w cia˛ gu ostatnich 200 lat i zmiany stosunków wodnych [The Problem of Dehydration of Wielkopolska Plain during the Last 200 Years and Changes of Water Conditions]. The Proceedings of the Conference: Ochrona i racjonalne wykorzystanie zasobów wodnych na obszarach rolniczych w regionie Wielkopolski [The Conservation and the Proper Use of Water Resources in the Agricultural Areas of Wielkopolska Region]. Urza˛ Wojewódski, Poznan´ , pp. 73–80. Klein E. 1973. Geschichte der deutschen Landwirtschaft im Industriezeitalter. Steiner, Wiesbaden, 192 pp. Kondracki J. 1991. Krajobrazy naturalne (Natural landscapes). In Starkel L. (Ed.) Geografia Polski. S´ rodowisko przyrodnicze [Geography of Poland. Natural Environment], Pan´ stwowe Wydawnictwo Naukowe, Warszawa, 670 pp. Kostrowicki J. 1973. Zarys Geografii Rolnictwa [An Outline of Agricultural Geography], Pan´ stwowe Wydawnictwo Naukowe, Warszawa, 631 pp. Kurnatowski S. 1975. Wczesnos´ redniowieczny prze l om gospodarczy w Wielkopolsce oraz jego konsekwencje krajobrazowe i demograficzne [The early medieval economic change in Wielkopolska and its landscape and demographic consequences], Archeologia Polski, 20, 1, 145–160. Meitzen A. 1869. Der Boden und die Landwirtschaftlichen Verhaeltnisse des Preussischen Staates nach dem Gebietsumfange vor 1866. Zweiter Band, Wiegandt & Hempel, Berlin, 571 pp.

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Mizgajski A. 1990. Entwicklung von Agrarlandschaften im Mitteleuropaischen Tiefland seit dem 19. Jahrhundert in energetischer Sicht. Beispiele aus dem Emsland und Wielkopolska [The development of the agricultural landscape on the Central European Plain since the 19th century: an energy-based approach. Examples from Emsland and Wielkopolska], Münstersche Geographische Arbeiten, 33, 110 pp. Mizgajski A., Kafel-G le˛ bowska K. 1990. Przeobraz· enia krajobrazu rolniczego od XIX wieku na przyk l adzie wsi Zamorze ko l o Pniew Wielkopolskich [Changes of the agricultural landscape since the 19th century with reference to the Zamorze village near Pniewy Wielko l olskie], Badania Fizjograficzne nad Polska˛ Zachodnia˛ , 41, A. Poznan´ , 75–85. Pianka E.-R. 1974. Evolutionary Ecology, Harper & Row, New York, 356 pp. Ryszkowski L. 1999. Ecological guidelines for development of sustainable agricuture in Poland. In Wicherek S. (Ed.) Paysages agraires et environnement. Principies ecologiques de gestion en Europe et au Canada, CNRS Éditions, Paris, 49–59. Ryszkowski L., Ba l azy St. 1999. Land-use change in the agricultural region of Wielkopolska, Poland. In Kroenert R., Baudry J., Bowler I.R., and Reenberg (Eds.) Land-Use Changes and Their Environmental Impact in Rural Areas in Europe, Man and the Biosphere Series, 24, UNESCO and Parthenon Publishing Group, Paris, 189–204. Ryszkowski L., Ba l azy St., Jankowiak J. 2000. Program zwie˛ kszania zadrzewien´ s´ ródpolnych (Shelterbelt Planting Program), Poste˛ py Nauk Rolniczych, 47(5), 83–107. Szulc H. 1972. The development of the agricultural landscape of Poland. Geographia Polonica, 22, Warszawa, 85–103. Szwed W., Ratyn´ ska H., Danielewicz W., Mizgajski A. 1999. Przyrodnicze podstawy kszta l towania marginesów eko l ogicznych w Wielkopolsce [Natural Foundations of Ecological Margin Modeling in Wielkopolska], Akademia Rolnicza, Poznan´ , 144 pp. Trampler T., Kliczkowska A., Dmyterko E., Sierpin´ ska A. 1990. Regionalizacja przyrodniczole´sna na podstawach eko l ogiczno-fizjograficznych [Regionalization of the Natural Forests according to the Ecological and Physiographical Conditions], Pan´ stwowe Wydawnictwo Naukowe, Warszawa, 159 pp. Wodziczko A. 1947. Wielkopolska stepowieje [Wielkopolska turns into Steppe] In (Wodziczko A. et al. Ed.) Stepowienie Wielkopolski [Wielkopolska turns into Steppe]. Part 1, Poznan´ skie towarzystwo Przjació l Nauk, Poznan´ , 141–152. Wojterski T., Wojterska H., Wojterska M. 1978. Potencjalna ros´ linnos´ c´ naturalna S´ rodkowej Wielkopolski [Potential Natural Vegetation of Central Wielkopolska], Badania Fizjograficzne nad Polska˛ Zachodnia˛ , 32, B, Poznan´ , 7–35. Wojterski T., Wojterska H., Wojterska M. 1981. Potencjalna ros´ linnos´ c´ naturalna dorzecza Baryczy [Potential Natural Vegetation of the Barycz River Drainage] (mapa 1:200.000) Pan´ stwowe Przedsie˛ biorstwo Wydawnictw Kartograficznych, Wroc l aw. Wos´ A. 1994. Klimat Niziny Wielko l olskiej [The Climate of the Wielkopolska Plain] [in Polish]. Wydawnictwo Naukowe Uniwersytetu im. Adama Mickiewicza, Poznan´ , 192 pp.

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CHAPTER

11

The Impact of Agriculture on the Environment of the Northern Parisian Basin Stanislas Wicherek

CONTENTS Introduction............................................................................................................263 Picardy — An Agricultural Region.......................................................................265 Open-Field Landscape ...........................................................................................268 Floods and Mudslides............................................................................................269 A Functional Ecological Agriculture ....................................................................271 Heritage ........................................................................................................271 Fertilizer and Pesticide Improvements and Their Impact on the Environment................................................................................................272 Environmental Risks ....................................................................................273 Acknowledgments..................................................................................................275 References..............................................................................................................275

INTRODUCTION In terms of global production, France is the leading European agricultural nation. French agricultural production accounts for 24% of all European Union production, making France (after the U.S.) the second largest agricultural producer worldwide. Most of this great agriculture is situated in the Parisian basin, and the northeast region of Picardy in particular (Figure 11.1). Agriculture has held an important place in Picardy for a long time. This ancient industry has left a multitude of traces in current structures, such as the predominance

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Photo 11.1

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Regions of study in France.

of grain production or the break up into relatively small plots in plateau regions. Throughout the 20th century, however, this agriculture passed through a period of spectacular evolution. Contemporary crop production (basically grain) is commercially oriented and entails intensive use of soils. Practices of all kinds have developed

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to ensure a permanent framework for farmers. Technical and agronomic means of production are increasingly intensive. However, does this modern, high-performance form of agriculture contribute to environmental management and sustainable development of the environment? Or does it, instead, contribute to the disruption of ecosystems, causing an impoverishment in the diversity of cultivations, flora, and fauna, by raising the risks of soil and water pollution? Finally, is its recent evolution responsible for ecological imbalances (Wicherek, 2000)? The major cultivations on the silty plains of northern Europe have, for several decades, experienced an intensification of soil erosion by water, giving rise to loss of soil fertility and harmful muddy floods. Yet neither the shallow typographic relief nor the limited erosion of the rains, which characterize these temperate regions of plains and hills, can explain the scale of these phenomena that one observed and measured in sloping agricultural basins. Moreover, according to the scientific literature, it would seem that no significant augmentation of the total rainfall or average intensity of precipitation (the common explanation for greater attacks upon the soils by rains) has been noted in these regions. However, most sloping agricultural basins affected by erosion problems have experienced a profound modification of cultivation systems and agrarian practices. Numerous studies show that the evolution of cultivation practices, due to the mechanization of agriculture, has led to diminished water infiltratability as well as augmented soil erosion (Boiffin et al., 1986; Wicherek, 1993; Le Bissonnais and Le Souder, 1995). In addition, agrarian practices, adapted to the modernization of agricultural production, are inadequate in relation to the morphologic soil characteristics (Lechevallier, 1992), thus favoring runoff and a loss of further possibilities for infiltration (Larue, 1992). If the changes in agrarian landscapes (in particular with the evolution from vegetation and utilization of soils) plays an undeniable role in the processes and harmful manifestations of soil degradation (Papy and Douyer, 1991), a historic approach is sometimes necessary to demonstrate and measure such evolutions over the long term. Documents produced by different state organizations, whether they be historic or current, effectively provide a record of agrarian landscapes over two centuries.

PICARDY — AN AGRICULTURAL REGION Amongst its forests, wooded valleys, stone and brick villages, and cathedral cities, Picardy possesses an open-field landscape that stretches over the chalky plateaus of the Parisian Basin, “la plaine” (“the plain”), as farmers call it. The SAU (surface agricole utilisée; agricultural area in use) covers nearly 71% of the territory. This region in the northern Parisian basin involves 15 billion French francs of business annually. It is also the top producing region in France for potatoes, sugar beets, and peas, and is the number two producer of wheat. In Soissonnais, one of its principal agricultural regions, grain (52% of the SAU) and sugar beets (21% of the SAU) are the primary crops, but corn (8% of the SAU) and peas (7% of the SAU) are also grown (Figure 11.2).

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A. 100 ha 50 ha

Soissonnais 85 ha 100 ha Picardy France 52 ha 37 ha 50 ha

1970 71 ha

1955 55 ha

1988 85 ha

100 ha 50 ha

B. NPK 300 u/ha

300 u/ha Picardy

200 u/ha

100 u/ha

NPK France

K

N PK

Figure 11.2

200 u/ha N 100 u/ha

P

(A) (left) Average French agricultural area (SAU) in Picardy and Soissonnais (Agreste 1991); (right) Increase in average SAU in Soissonnais farmlands — 1955, 1970, 1988 (RGA, 1955, 1977, 1988). (B) Consumption of N, P, and K in France and Picardy.

Picardy, particularly Soissonnais, is also distinguished by its large area farms. The average farm size is 37 ha for all of France, 52 ha for Picardy, and 85 ha for Soissonnais. In Picardy more than 45% of farms cover more than 50 ha. In Soissonnais, the large size of farms is not a new phenomenon, since the average SAU per farm exceeded 55 ha in 1955, was 71 ha in 1977, and 85 ha in 1988 (Figure 11.2). Farms are frequently larger than 300 ha (with a record area of 5,000 ha) although the average is lowered by smaller market farms, animal farms, and the mixed farming of the valley floor. The region is also distinguished by a higher consumption of fertilizers than the national average, whether this be for the separate elements N, P, and K, or for the total NPK: 200 u/ha in France vs. 308 u/ha in Picardy (Figure 11.2). Added to this is an imposing fleet of agricultural machines. After a strong increase in the 1970s, the number of tractors today stands at an average of 2.7 per farm. In 1988, 60% of farms had at least two tractors. From 1970 to 1988, the number of 110 CV tractors has tripled; on average there is one tractor for every 28 ha and one agricultural worker for every 100 ha. The combination of this mechanization and sizeable consumption of fertilizers is associated with yields higher than the national average (Figures 11.3 and 11.4). Since the beginning of the 20th century, the average yield of wheat in France has almost always been surpassed by the average yield of wheat of one farm on the Soissonnais Plateau (the current plateau average is still higher than the average national production). This rise in yields since the beginning of the 20th century also relates to potatoes and sugar beets. Production of the latter crop has more than doubled and today exceeds 60 t/ha, representing an extraordinary increase.

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100 90 80 70 60 50 40 30 20 10 0

267

1994

1988

1982

1976

1970

1964

1958

1952

1946

1940

1934

annual average in Soissonnais farmlands

1928

Yields in qt/ha

IMPACT OF AGRICULTURE ON ENVIRONMENT OF NORTHERN PARISIAN BASIN

French average yields Average yields in a Soissonnais farmland (Picardy) Figure 11.3

Growth in wheat yields. Comparison of France and Picardy. (From SNIE, 1993; farmer archives.)

Beets

Wheat

Potatoes K

Maize

N

200 u/ha

200 u/ha

K

K

N PK

100 u/ha N

PK

N

PK

N P

N

P

P

NP K

N

P

K

100 u/ha

1950 1995 Figure 11.4

Comparison of NPK consumption in 1950 and 1995 (from investigations).

Agricultural crops and related industries are widely developed locally (production of sugar, potato flour, dehydrated mashed potatoes, potato chips, frozen French fries, etc.). They also include other vegetable production, such as high protein plants (peas, flageolet beans, etc.), carrots, and onions. In the Picardy region there are also numerous sugar refineries (Beghin Say, Générale Sucrière, CFS, etc.) and Vico (at Vic-sur-Aisne), D’Aucy, Bonduel, Findus, Saupiquet, of Flodor, Unichips and Mc-Cain, to cite only the best-known examples. Sugar agriculture — “a world apart” (Lefèvre, 1993) — represents a colossal organization that directs all stages of production — from the seed provided to the farmer to the sugar cube, passing through the date of crop sowing, date and type of treatments, and the planning of the harvests. Sugar is of major importance in the region: out of 437,000 ha of sugar beet planted in France, 36% are in Picardy. Of the 46 sugar refineries located in France, 16 are in Picardy. This crop, thanks to

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significant scientific and technological means, has undergone a considerable evolution in the course of the last 20 years (comparable to the progress in use of pesticides). The same remarks also apply to potatoes. For a long time, this cultivation — for potato flour and direct consumption — developed spectacularly in the 1950s and is surrounded by an industrial structure comparable to that of sugar beet production. From this perspective, the Picardy region, more than any other, is representative of the development of cultivations of foodstuffs and the production structures that accompany them. One may wonder whether this spectacular development (dating essentially from the second half of the 20th century) is responsible for a modification of landscapes (Wicherek, 1999), of fertilization, or of agricultural mechanization?

OPEN-FIELD LANDSCAPE Yields have increased considerably, potato cultivation has greatly developed, and the sugar beet industry has perfected itself, but one observation stands out: the changes in the agrarian landscape and the size and distribution of plots of land are not extraordinary (for example, Soissonnais Plateau, according to the study of aerial photographs). Observations about the plateau indicate that, on the whole, the plots of land and open-field landscapes had already occurred under François I. Whether in 1936, 1958, or 1991, it was plots larger than 5 ha that dominated. The overall plot size enlargement naturally benefits large plots, those larger than 20 ha, for example, at the expense of those of less than 5 ha. This can be explained in two ways: first, the disappearance of small gardens given to agricultural workers for their personal vegetable production (sources of weeds — they disappeared around 1950, the producers preferring to compensate workers by distributing a part of the farm production); second, the enlargement of border plateau plots or converted former pastures. Over the whole of the township, from 1936 to 1993, not one hedge disappeared, for the simple reason that there were none. Elsewhere in the Soissonnais, very few townships were regrouped because there was no reason to do so. The large farms at the beginning of the 20th century provided a means of living for about 100 people, people who often lived in housing estates adjoining the farms. Production was also more varied than it is today. At the beginning of the 20th century, most farms included a flock of sheep (sheltered in a sheepfold during the winter, they were moved to pastures in the spring and after the grain harvest, where they grazed on stubble). Therefore, the removal of stubble occurred rarely or not at all. An element conducive to the low erosion of bare soils in autumn but not favorable to the cleanliness of the land, direct ploughing of the stubble occurred later and lasted longer because of the slowness of animal haulage (draft horses and oxen). The oxen consumed the beet pulp, straw, and hay; the horses consumed oats and alfalfa. The disappearance of these animals occurred earlier in this area than in the rest of France — resulting in the disappearance of fodder production, intended for animal feed, around the 1950s. For example, alfalfa and oats (which represented about 15% of the land worked) disappeared with mechanization and the consequent disappearance of draft animals (animal breeding ceased completely around 1960). The cultivation of wheat, peas, beets, and potatoes then expanded. The production of the latter crops then greatly surpassed

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needs for local consumption. From the 1960s, potatoes were grown for industrial uses (either for food or for potato flour production). The same is true of peas and legumes. The transition from use of draft animals to mechanization and from fodder cultivation to industrial crop cultivation was rather slow since it took place over a period of about 20 years. However, the division of the land remained constant from the beginning of the 20th century until today. Where there is no evolution of the plots of land, one can trace the division back to the heritage of the Soissonnais Plateau where the farm origins are very old. In the Middle Ages, numerous forms of farms already existed under the supervision of the Prémontrés and the Cistercians — such as the farm of Montramboeuf, or the farm of the Château, which still exists today in the commune of Vierzy. The farms of this township seem even to have descended from Gallo-Roman villae (archaeological vestiges), linked to the presence of the Brunehaut Way, a road joining Lutecia to Soissons. In addition, at the time of the Revolution the limits of property and of plots of land were spared. Another historical factor is pertinent — over the course of the centuries this region was crossed by waves of successive invasions by foreign armies. Clearly, it never presented a farmland intersected by hedges and trees as in the west of France. The great bare plateaus forced the enemy to expose itself. Very little wooded area existed; what wooded areas were there totally disappeared, as did rabbit warrens and groves of trees, with the onset of mechanization, during the 20th century.

FLOODS AND MUDSLIDES Few studies on soil erosion have been carried out in the departments bordering the Seine valley (Wicherek, 1993; Papy and Douyer, 1991). This region is less affected by water erosion than is the rest of France. A preliminary understanding can be based on the analysis of the number of townships affected by natural disasters, such as floods and mudslides, which in agricultural areas are the principal consequences of the waterproofing of different pedological horizons and soil losses (Meyer et al., 1999). Several hundred reports of natural disasters were published in the Journal Officiel, following the law of the 13th of July, 1982. After reviewing the declarations of natural disasters occurring in the departments (Yvelines, Eure, Eure-et-Loir, Val d’Oise, but also Seine-Maritime, Oise, and Aisne), it is possible to establish certain statistics. Among these departments, about 95% of the townships became disaster stricken following floods and mudslides, only 3% of which following floods of the Oise or of the Seine (1993–1995). Furthermore, 63% of the townships are situated in rural areas, but 5% are located in urban zones where the impermeability of the land and the insufficiency of the rainwater purification network constitute the most probable explanatory factors for the damage incurred (Figure 11.5). The numbers of flood and mudslide-type disasters are also highly variable from year to year. A 15-yr period is still insufficient to detect a possible increase in flood frequency — at least as far as the northwest Parisian basin is concerned. The monthly frequency of mudslides and floods over 15 years is 43% for December 1993 and January 1995 and 46% for May through August during the same period. The frequency of notification by stricken townships during the end of spring and the summer

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Figure 11.5

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Example of damage resulting from erosion and pollution in a beet field in Erlon, northern Parisian basin (a station of measures belonging to the Center BIOGEO, CNRS/ENS). (From F. Tellier, June 1999.)

nonetheless reaches 75% even if the two floods of 1993 and 1995 are eliminated from the chronological series. During this low-water period, floods by sheet overflows or water runoff have a much lower frequency than muddy floods or those not provoked by runoff rainwater pouring along slopes following storms. Nevertheless, these same slopes show welldeveloped vegetal cover, a factor that inhibits runoff. It is probable, as a result, that the intensity and the localization of storm-type summer rains are determining factors. So it would seem that the events related to hydric surplus are due as much to runoff as to overflow of water courses. Alternatively one can imagine asking about a possible correlation between the number of disasters occurring during a summer period and those occurring during the preceding winter. A winter marked by a great number of natural disasters probably corresponds, in fact, to high pluviometric totals having favored the genesis of floods by the extension of areas contributing to the outflow of the flood. And the high winter pluviometry combined with little vegetation during “inter-cultivations” frequently provokes a rapid degradation of soil surfaces and the appearance of sedimentary crust (Boiffin et al. 1985). Although a succession of cycles of desiccation and wetting during the spring is likely to destroy the crust and thus reestablish better infiltration, one may wonder about the role of the soil surface quality in the instances of flood disasters following storms during the summer. A winter during which many townships were affected by floods following major precipitation events is not, however, necessarily followed by a summer with a high number of events; of five disastrous winter periods, three were followed by a summer marked by a high number of flood cases. Conversely, five eighths of the disastrous

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summers were preceded by winters without harmful events. So it would seem that the frequency of more or less muddy floods occurring in the summer is not unlike, in the northwest Parisian basin, the number of flood and mudslide disasters occurring during the preceding winter. Could erodability due to rain erosion have an effect on the formation of disastrous runoff? If these results are given a more in-depth analysis, however, they reveal a conceivable step. The chronological series also permits an interpretation of possible spatial heterogeneities in the instances of natural disasters linked to hydric surplus. The departments of Eure-et-Loir and Yvelines are two times less affected than are Eure, Oise, or the Val d’Oise and six times less affected than Seine-Maritime, where the Pays de Caux and the Seine valley appear to be the most affected. If the events had been measured, analyzed, and then explained in the Pays de Caux, Soissonnais Plateau, would it not be interesting to try to understand the “non-events” in the nearby departments of Eure-et-Loir and Yvelines? The spatial-temporal analyses of the non-event are often ignored in the study of morphogenic processes. In the framework of station measures to an outlet of the primary sloping basin, it can be observed frequently that the conditions for the formation of runoff — or lack thereof — although conditions presumed are filled, are not explained. Is there not, in this case, proof of the omission, or underestimation, of one of the explanatory factors of runoff formation? Thus, the analysis of the “nonevents” permits a readjustment in hypotheses and factors initially considered. In the seven regional departments studied, vegetation and soil use do not seem to influence the occurrence of mudslides (Wicherek, 1988). Indeed, of those seven departments, the Pays de Caux constitutes the agricultural region that was most affected by mudslides and that also has the greatest percentage of area grass covered in relation to the SAU. Inversely, the two least-affected departments — Eure-et-Loir and Yvelines — are the departments with the highest percentage of arable land. Consequently, it is probable that the frequency of damage caused by mudslides is independent of the state of the surface and soil use at the level of the department. However, would not the Pays de Caux have experienced, over the course of recent decades, more profound modifications of its agrarian landscapes than the cultivated plateaus of Yvelines and western Eure-et-Loir? The difference in the effect of floods and mudslides on northwest Parisian basin departments may be explained not only by the differences in geomorphologic, pedologic, and climatic conditions but also by the rhythms of evolution of farming practices and agrarian structures, hence the interest in historical research that provides analysis of the influence of agrarian landscape transformations on the imbalances of the physical milieu. Mudslides and water erosion are expressions of these imbalances. A FUNCTIONAL ECOLOGICAL AGRICULTURE Heritage The large farms of the past, composed of large plots, covering large areas and at the forefront of French agriculture for several centuries, are hardly different from others. Of course, there are differences linked to the division of plots or to the variety

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of agricultural yields, but overall they had reached the same degree of productivity: fertilization, pesticides, and yields were very similar to those of other major agricultural regions. The 20th century was a century of changes toward a commercially oriented agriculture and toward agrarian capitalism (Fiette, 1995). The man who works the land today has a farm that is 4.5 times more productive than that of his father in the 1960s; at the same time, the number of people so employed has been halved. Demonstrating a desire for competitiveness, farmers eliminated animal rearing and its accompanying crops, such as oats, and specialized in the food processing industry. Today’s farmer often has no hesitation about designating his farm as a business farm from which he makes a profit. Fertilizer and Pesticide Improvements and Their Impact on the Environment Although the agricultural landscape has evolved very little, mechanization has, by contrast, made great leaps. Trucks were used for sugar beet harvesting beginning in 1930, but new machines for making pesticide treatments easier, such as the herbicide pulverizer, came into use around 1913. During World War I, steam locomotion was introduced to compensate for the lack of manpower. It was a system of winches and pullies connected to a steam-powered machine. This system was replaced first by the caterpillar tractors and then by the pneumatic tractors. Beginning in 1944, pneumatic tractors became widespread due to the arrival of American surplus machines. Soil fertilization using manure is a longstanding practice in the region (Brunet, 1960). Farmers in the olden days were well known for their savoir-faire, for their means, and their example-setting; the Cistercians were already improving the manuring of land. Following the serious financial crisis of 1880, when the price of wheat did not rise, the only solution was to increase crop yields. This began in 1900 with the use of mineral fertilizers, which had appeared several decades earlier. For example, bills preserved at the Parcy Farm in Soissonnais show that in 1926 sodium nitrate and super phosphate mineral were used. By 1950, the use and nature of fertilizers had evolved little. Soluble mineral compounds (widespread today) were being used, but so too were solid compounds such as scoria, already used during the 19th century. The 1970s were a turning point, marked by both a great increase in use of mineral fertilization and the quasi-disappearance of other types of fertilization. Today, wheat, potatoes, and beets are more fertilized than they were in 1950 (Figure 11.6). The situation is more or less the same for pesticides. At the beginning of the 20th century, they were used widely in Picardy but the types were totally different. For example, for wheat in 1926, copper nitrate (rather expensive), cuproazotine, or sulfuric acid could be applied. Beginning in the 1970s and continuing today, synthetic products, with numerous and frequent applications, are used. Examples are isoproturon (grain herbicide) and metamitrone (sugar beet herbicide) or chloridazone (Figure 11.6). If pesticides used seem less for corn, they are nonetheless very persistent and often noxious, for example, atrazine and lindane, which are often detected in drinking water and are hazardous to human health.

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Sugar beets (from April to June)

Potatoes (from April to August)

273

20

Wheat

10 (from April to June)

Peas (from May to June)

10 Maize (from March to July)

Herbicide, examples isoproturon and 2,4 mepa on wheat, metamitrone and chloridazone on beets Insecticide, examples endosulfan on potatoes, lindane on maize Fungicide, examples bentazone and mancozebe on potatoes Various, examples shortening cymectacarbethyl on wheat

Figure 11.6

Present number of pesticide treatments (from investigations).

Environmental Risks In considering their farms as businesses, farmers (agricultural businessmen), adopt cultural practices that create risks for the environment. Indeed, the coexistence of environment and agriculture is a difficult one. Years of productivity are emphasized as the basis of use of marked environmentally unfriendly practices. For several years, farmers have been attacked on all sides; they are called polluters or reactionaries, and they are widely accused of attacking the environment. Reasons given are the intensive monoculture on large plots and the excessive use of fertilizers and pesticides. In Picardy, soil erosion comes from a very real situation, the same as the degradation of surface water and ground water from the chalk layer (Angéliaume, 1996). Cultivated soils suffer from repeated water erosion (encouraged by the packing of soils by agricultural machines and by spring crops such as beets, corn and potatoes). Chronic winter erosion, or occasional spring erosion, damages crops and the soil (impoverishment of fertile silt and organic matter). It also contributes to the pollution of waterways that receive the runoff waters filled with suspended matter, fertilizers, and pesticides, all dangerous for piscicultural life (Wicherek, 1999, 2000.) Fertilizers and pesticides may be found in strong concentrations in surface waters, as indicated by results taken from a study of sloped basins (Figure 11.7). Water runoff samples taken during the course of two storms register concentrations of nitrates (10.6 to 13.1 mg N/l) close to the authorized limit for drinking water (11.3 mg N/l). A more critical fact may be observed regarding pesticides. Lindane and atrazine, whose use is currently regulated, are found in very high concentrations regardless of the date of the runoff. Note that the authorized mean for atrazine is 0.1 ug/l, and nearly 3,000 times that concentration was measured in water in May, 1994. Added to this atrazine and lindane (as opposed to metamitrone and chloridazone) essentially circulate in soluble form (80 to 90%, as opposed to 5 to 10% for

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May 24, 1994 NO3 =10.6mg N/l PO4 = 0.689mg P/l P total = 37.22mg P/l

NO3 =13.1mg N/l PO4 = 0.802mg P/l P total = 22.2mg P/l

lindane = 0.21µg/l atrazine = 8.9µg/l metamitrone = not detected chloridazone = not detected

lindane = 1.9µg/l metamitrone = 0.87µg/l chloridazone = 6.22µg/l

Lindane: maize insecticide, atrazine: maize herbicide metamitrone and chloridazone: beet herbicide Figure 11.7

Examples of pollutant concentrations in runoff waters. (Angéliaume 1996.) 2

Biomass (mg/m2)

Density (individuals/m )

30

Fallow 32.4

Wheat 21.6

20 10

Beets 3.2

Fallow 32.4

30

30

20

20

10

10

Wheat 21.6

30 20 Beets 3.2

10

Dominant families (Carabidae, Lassidae, Cypselidae, Cantharidae, Muscidae, Staphylinidae)

Figure 11.8

Examples of impacts on cultural practices concerning biodiversity. (J. Karg 1996, in Angéliaume 1996.)

metamitrone and chloridazone) and are thus easily dissolved and washed toward waterways. Pesticides can also influence the microfauna present in cultivated plots. The nature of these pesticides in relation to the cultivation is very important. Whether measured in microbial density or in biomass, biodiversity is markedly lower in beet fields (with repeated and apparently more noxious treatments) than in wheat and fallow fields (Figure 11.8). Picardy agriculture is a high-performance (yields, rank in French production, growing practices, technical experimentation, etc.), modern (high technological means), export (brasserie barley, bread-quality flour, etc.) agriculture, but can it be qualified as clean and environmentally friendly? Can it be used as a model? It is difficult to imagine that it is when one considers problems such as erosion, water quality degradation, and the attack upon insect biodiversity. A change toward a cleaner agriculture seems even more difficult because of the current political and European contexts. It is thus probable that the different rhythms of evolution in the agrarian landscapes in the northwest Parisian basin can explain the interdepartmental heterogeneity of flood and mudslide frequency in rural areas (Wicherek 1999). The permanence of agrarian landscapes in former grain-growing regions and open-field regions, such as Mantois, serve in the northwest Parisian basin to moderate

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the consequences of runoff and water erosion. This situation does not seem to occur north of the Parisian basin, where the occurrence of mudslides can be explained (among other reasons) by the expansion of crops favorable to runoff and erosion, such as sugar beets, potatoes, and endive. Even if the disappearance of hedges, woods, ponds, and meadows has greatly contributed to the worsening of the effects of runoff and water erosion, which is verifiable for former regions, it cannot, however, be applied blindly to all of France’s agricultural regions, in particular those marked by a relative stability in the principal elements of the agrarian landscape. It thus seems essential to take into account the long-term evolution of agrarian landscapes in studies treating the links between agriculture and the environment. The last 20 years have been a period of stress for French agriculture: 1975, the crisis of “les trente glorieuses,” then the PAC, then PAC reform. In Picardy, the agricultural situation remains full of contrasts: the coexistence of a small farm in the Aisne valley with its few cows, each named after one of the farm’s creditors, and the immense farms on the plateau near Chemin des Dames, of several hundred hectares, which are villages within themselves. Large-scale cultivation, although affected by problems (drop in land prices since 1980, terres gelées, after years of productivity, difficulty of accepting fallow fields and other brakes on production) has been to a great degree spared by the crisis shaking the agricultural world today. The tendency is toward the stabilization of fertilizer and pesticide consumption, but not toward reduction. These products have brought about a spectacular rise in yields, growth that was even more pronounced on the large farms of the plateau. It is difficult to win acceptance for a drop in consumption, which is considered a step backward. Yet at the present time, with the set-aside, the notion of yields is often discussed. In the best of cases, growers can treat their fields with the objective of equalizing the cost of production and yields. They practice what is called reasonable treatment (prevention and treatment), but only of what is necessary, when it is necessary. It is difficult for them to reduce treatments because preservation of farm revenue depends upon maintaining the productivity acquired in past decades. By this very fact, this agriculture, still high performing, remains a source of damage to the environment and remains relatively reserved toward new agro-environmental developments.

ACKNOWLEDGMENTS The author acknowledges the collaboration of M.O. Boissier, A. Sevestre, and A. Angéliaume.

REFERENCES Angéliaume, A. (1996) Ruissellement, érosion et qualité des eaux en terre de grande culture, études de cas en Laonnois et en Soissonnais. Thèse, Université Lille I, 488 p. Angéliaume, A. and Wicherek, S. (1998) Cultivated soils erosion and agro-pedological consequences. Example: Picardie-Parisian Basin. 16e Congrès Mondial de Science du Sol, 20–26 août 1998, Montpellier, CD Rom, symposium no. 31.

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Angéliaume, A. (1999) Paysages et pratiques agraires dans le nord du Bassin parisien. Evolution du début du siècle à nos jours et impacts sur l’environnement (exemple du Soissonnais) pp. 101–114. In Paysages agraires et Environnement, S. Wicherek, Ed. CNRS Editions, 412 pp. Boiffin, J., Papy, F., Peyre, Y. (1986) Systèmes de production, systèmes de culture et risques d’érosion dans le Pays de Caux. Rapport INA-PG/INRA/Min. Agri., 154 p. + appendices. Brunet, P. (1960) Structure agraire et économie rurale des plateaux tertiaires entre la Seine et l’Oise. Thèse d’Etat, Université de Caen, 552 pp. Fiette, A. (1995) L’Aisne des terroirs aux territoires. Comité d’expansion de l’Aisne, Compagnie Européenne de reportage et d’édition, 286 pp. Karg, J. and Ryszkowski, L. (1996) Animals in arable land. In Dynamics of an Agricultural Landscape. Eds. Ryszkowski, N. French, A. Ke˛ dziora. PWRL Poznan´ , 138–172. Larue, J.P. (1992) L’érosion des sols cultivés dans la région de La flèche, le rôle de l’évolution du paysage rural et des façons culturales, in Bull. Ass. Géogr. Fr., 2, 127–134. Le Bissonnais, Y., Le Souder, C. (1995) Mesurer la stabilité structurale des sols pour évaluer leur sensibilité à la battance et à l’érosion, in Etude et Gestion des Sols, 2, 1, 43–56. Lechevallier, C. (1992) Evolution des structures agraires et érosion des sols en Pays de Caux, in Bull. Ass. Géogr. Fr., 2, 101–106. Lefevre, D. (1993) Le retour des paysans. Le cherche Midi Ed., 334 pp. Meyer, E., Wicherek, S. and Peulvast, J.P. (1999) Processus de dégradation des sols et évolution des paysages agraires depuis le XVIIIe siècle. Exemple du nord — ouest du Bassin parisien. In Paysages Agraires et Environnement, S. Wicherek, Ed. CNRS Editions, 412 pp. Papy, F. and Douyer, C. (1991) Influence des états de surface du territoire agricole sur le déclenchement des inondations catastrophiques. Agronomie, 11, 201–215. Wicherek, S. (1998) Les relations entre le couvert végétal et l’érosion en climat tempéré de plaine, exemple de Cessières (Aisne, France). Z. für Geomorphologie N.F., 32 (3), 339–350. Wicherek, S., Ed. (1993) Farm Land Erosion in Temperate Plains Environments and Hills. Elsevier, Amsterdam, 584 pp. Wicherek, S., Ed. (1999) — Paysages agraires et environnement. Principes écologiques de gestion en Europe et Canada [Agrarian Landscapes and Environment. Ecological Principles of Management in Europe and in Canada]. CNRS Editions, 412 pp. Wicherek, S. Ed. (2000) L’eau de la cellule au paysage [Water, from Cell to Landscape]. Elsevier Editions, UNESCO, Paris, 424 pp.

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CHAPTER

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Models Assessing the Impact of Land-Use Change in Rural Areas on Development of Environmental Threats and Their Use for Agricultural Politics Armin Werner and Peter Zander

CONTENTS Introduction and Objectives...................................................................................278 Sustainable Development of Rural Land Use.......................................................278 Decision Making for Solving Complex Problems of Rural Areas.......................280 Models for Assessing the Impact of Land Use and Land-Use Changes .............282 Modeling the Development in Land Use ....................................................282 Assessing with Models the Impact of Land Use on the Environment .......282 Approaches of Modeling Land Use and the Effects of Land Use .............283 Concepts for Landscape Models......................................................283 Modeling Spatial Aspects ............................................................................284 Applying Models for Optimization of Land Use............................285 Decision Making for Land Use Planning in Rural Areas through Multi-Objective Optimization — An Example ...................................................285 The Multi-Optimization Model ...................................................................286 Simulations for the Study Area ...................................................................289 An Outlook with Scenario Studies of Agricultural Politics........................290 Perspective....................................................................................................292 Acknowledgments..................................................................................................294 References..............................................................................................................294

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INTRODUCTION AND OBJECTIVES Especially in industrialized nations, changing economic conditions lead to large structural transformations in the businesses of land and its use (agriculture, forestry, in-land fish production, etc.). These transformations stem from changed politics of land use resulting from the diminishing importance of the land-use business within overall business and from economic and possibly climatic global change. Public perception of land use is also changing. More and more often not only is the supply function (food, fiber, wood, etc.) addressed, but continuously increasing ecological goals are proposed for land use and land-use planning. The changes in these driving forces will lead to changes in land use and thus in the impact of land-use systems on rural areas (economy, social aspects) as well as on the ecology (abiotic sources, nature). Due to the complex interactions of land-use systems with the relevant economic, cultural and ecological indicators, it is necessary to address the resulting problems of current or future land-use changes in an integrative way — integrated land development (Thöne, 2000). Integrated rural planning therefore can serve as an example of methods and approaches that help to achieve a sustainable development in human activities (Werner and Haberstock, 2001). The sustainable development of rural areas is a major goal of the national and international politics that are related to nonurban areas. Most rural areas are dominated by agricultural land use. Therefore, the impact of agricultural land-use systems on the environment can be substantial. Assessing that impact on the environment is crucial for sustainable rural development. But in order to understand and control that impact and other relevant indicators, it is necessary to develop new methods for assessing the impact of land use and technologies and therefore of land-use politics or other relevant driving forces. These methods have to deliver general answers, that are scientifically sound and that can be generalized but still are transferable to the specific conditions of the studied area. The cooperative character of studies on future land use requires expert knowledge and innovative methods to analyze complex empirical data and to allow for the analysis of possible futures. Many difficulties in the management of complex systems can be overcome with the use of decision-making support systems. This chapter summarizes and discusses methods to assess the impact of changing land use with models. An extensive example of the multi-criteria optimization approach shows the possibilities of using such a system in decision making for economic-ecological problems in rural areas.

SUSTAINABLE DEVELOPMENT OF RURAL LAND USE Agrolandscapes are an integrated product of human actions, of agrotechnical, political, and ethical character (Mansvelt, 1997). Minor or drastic changes in land use, therefore, can always have implications for the entire complex system of an agrolandscape. Consequently, it will be necessary to address and evaluate simultaneously

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several processes and values when the impact of technologies or agricultural politics has to be assessed. A common ground for defining a model for future land use is the sustainable development of land use and thus of rural areas which is sustainable land development (Werner et al., 1997). Economic and ecologic, as well as social and cultural, goals should be fulfilled (Barbier, 1987, Goodland, 1996). With these goals in mind, integrative tools are necessary that support the decision-making process in rural areas and the related land-use planning (Maxwell et al., 1999). It is especially difficult to assess the impact of land-use systems on the environment of agrolandscapes (the complex of abiotic compartments and the nature). First, those indicators (values or objects) that should be addressed in the evaluation process are not yet sufficiently defined and agreed to (Maxwell et al., 1999). These indicators have to be selected by the affected stakeholders, the groups that participate in the decision-making process, or by society in general. Which indicators are suitable can be suggested by scientific evaluation through joint processes of different disciplines (Mansvelt, 1997). Second, it is necessary to have methods for deriving the values these indicators will have under specific land-use conditions. With this information, decision makers can select the feasible options in land use and landscape planning. Many national or transnational (e.g., from the European Union) concepts related to the development of rural areas have similar approaches (Bosshard, 2000). They include: • • • • • •

Strengthening regional marketing and food processing Enhancing the competitiveness of regional business Improving the social or cultural activities within a region Attempting to close regional matter cycles Preventing pollution of abiotic compartments Protecting and developing sensible biotopes as regional habitats for typical species

The character of these elements represents remarkably the necessary ingredients of the general concept of a sustainable development (Thierstein and Walser, 1997). For the groups and people who participate in the planning and running of a region, the common base is the available space and the natural resources of that region. There are no accepted and standardized methods available for defining all relevant groups for this participatory process of decision making and planning. Even intuition can be a crucial element of identifying the relevant stakeholders or actors (Baeriswyl et al., 1999). Successful decision making for rural development needs a systematic procedure and needs to be restricted to the relevant processes or compartments of the respective system, the rural area. One approach is to identify the necessary and important functions that have to be fulfilled within the rural area. For an integrated region-oriented policy, Kolk et al. (1999) identified 12 main categories of relevant functions of these landscapes: housing, utilities, agriculture, fisheries, industry, mining, services, retailing, transport, recreation, conservation and protection. In many regions this should be extended with the category of forestry. For this chapter, the focus is on agriculture, conservation, and protection.

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DECISION MAKING FOR SOLVING COMPLEX PROBLEMS OF RURAL AREAS The process for establishing sustainable rural development cannot be handled today by the traditional steps of rural land management: design and reconstruction of the area. Today it is mainly a problem of communicating with the relevant people or groups within the region and deciding how to let them participate in the decisionmaking process: “Implementation of policy objectives and targets is not likely to happen, without serious local participation and commitment” (Volker, 1997). This leads to the conclusion that integrated rural development is possible only with a democratic approach, from the bottom up (Meyer, 1997). For this purpose, round tables (Müller et al., 2000), environmental cooperatives (Glasbergen, 2000) and innovation groups (Horlings et al., 1997) are relevant instruments to determine and manage conflicting goals for the development of rural areas. In terms of ecological goals, recently the main focus of land-use development was on minimizing the impact of agriculture and forestry on the abiotic compartments of the environment (water, soil, atmosphere). Today increasing attention is directed toward goals that include, to a large extent, the living parts of agricultural landscapes (Harms et al., 1998). Rural areas have a good chance to achieve sustainable development when • instead of being driven mainly by exogenous business processes, endogenous forces dominate • the perspective of business and administration changes from sole consideration of static-site factors to chance and possible developmental processes • the perspectives in the region switch from economic forces to human action and initiative (Thierstein and Walser, 1997)

The last point in particular leads to the necessity of specific decision-making methods for rural areas. These methods should help stakeholders define possible solutions or pathways in the development (scenarios) and analyze the outcome of these solutions with respect to the views of all involved disciplines and groups (economy, ecology/nature conservation, social and cultural aspects). The process of defining objectives, assessing the impact of different land-use strategies, and eventually redefining those objectives will be repetitive and cyclic. Decision making for the development of rural land use has to be participative and iterative (Werner and Bork, 1998). The most promising way to achieve all these goals is to jointly define scenarios and assess the impact on the economy and ecology with simulation models (Figure 12.1). This leads to a change in the paradigms of land-use planning and land development with severe impacts on the related sciences, rural politics, consultation business, and regional or national administration (Magel, 2001). However, one always has keep in mind that this recursive or heuristic approach of assessing the impacts of land use cannot generate a “general truth” or “the only best solution” (Bosshard, 2000). The result of such decision making, or designing of rural development and rural politics depends on the involved people and the actual scientific knowledge. But “these results are independent of the existence of generally

Region

t1 . . . tm

1 . . . m

o1 . . . om

organisation p1 . . . pm

size

Farm 2 a1 . . . an

1 . . . n

b1 . . . bn

wheather

yield potential f(a,b) c1 . . . cn wheat wheat wheat wheat ... ...

1 1 1 1 1 1

Farm 2

cost z1 z2 z3 . zk

P2 x21 . . . x2k

P3 xl . . . xlk

Farm 3

Farm 1

Evaluation and visualization Geographic Information Systems

P1 x11 . . . x1k

Resources \ Production techniques

low low high high ... ...

intensity large small large small ... ...

scale scale scale scale

technique

production farm income employment

Farm 2

Economic results

Ecological evaluation

Gross margin calculation

crop

site

Site specific production practices

Multiple Goal Linear Programming Farm model 1-r

soil

Nr

Site characterization

From site and farm typology to a regional evaluation of land-use scenarios (From Zander and Kächele, 1999.)

biotic indicators abiotic indicators

Farm 3

Farm 1

Ecological results

Figure 12.1

type

Nr

Farm typology

Farm 3

Farm 1

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accepted moral axioms or principles” and therefore represent a nonauthoritative approach (Bosshard, 2000).

MODELS FOR ASSESSING THE IMPACT OF LAND USE AND LAND-USE CHANGES Modeling the Development in Land Use The specific situation of land use in a region is a result of the interactions of site conditions (natural productivity — i.e., soil, climate, water supply — type of business activities, infrastructure, etc.) and economic driving forces or conditions (politics, prices, assessable markets, environmental restrictions, available and permitted technologies, etc.) with the decision making of the land users. Much literature is available that describes procedures and models with which development of agricultural and forestry land use can be determined under changing conditions. Most models were developed for analyzing the possible development of agricultural or forestry business sectors when prices, markets, technologies or other economic conditions change (Bouma et al., 1998). Recently, the predicted global changes of climate or economy are also the objective of the development of such models (e.g., Mirschel et al., 1995). Most of these approaches are used to analyze the agricultural business. Recently such sectoral models have been broadened stepwise toward additional analysis of the impact of land use on environmental indicators (Wiborg, 1998). No integrated models are yet available to estimate or analyze the entire set of different functions of land use (see part 2 of this chapter) in a region at once. But such a holistic approach is necessary in order to answer questions related to the complex system of land development (Baumann, 1997; Buchecker, 1997; Ittersum et al., 1998). The impact of land use changes is the main focus for developing complex landscape models. These models provide scenario studies, describing the land-use situation that can be expected in the future under a set of different conditions with defined changes in the driving forces (Bork et al., 1995). Assessing with Models the Impact of Land Use on the Environment The environmental impact of land use can be analyzed in different ways. The main reason for doing this is to analyze different scenarios of land use. Because most specific situations to be analyzed do not yet exist, it is not possible to use classic scientific approaches of observing and measuring. It therefore is necessary to estimate or predict the relevant situations of land use with tools that are general and that are capable of considering the specific situation of the region, its economic and environmental conditions. Currently this kind of analysis can be accomplished only with specially designed and developed simulation models (Wenkel and Schultz, 1999). These are computer-based tools that derive the conditions of relevant indicators with reasoning or calculations. The main problems of designing and using such tools lie in minimizing the amount of necessary input data and reducing the

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level of detail for the causal or indirect description of compartments or processes. Depending on the goals to be achieved, more or less sophisticated tools are developed: simple approaches that balance relevant flows of matter, nutrients, or energy (e.g., Bach, 1987); models that consist mainly of conditional clauses, rules, or table functions (e.g., Bork et al., 1995); models that describe the relevant processes in depth (e.g., Worral and Burt, 1999); or very complex models that look for a large set of indicators in detail (e.g., O’Callaghan, 1995). Models that should help to analyze the complex impact of land use on relevant ecological indicators have a special demand for spatial data or they even have a spatial design (Costanza and Maxwell, 1991) because many ecologically relevant processes do occur as spatial interactions between compartments of a landscape (e.g., lateral flow of water, nutrients, matter, energy or migration of organisms). But the spatial interaction of business structures or human beings also has to be regarded when the whole landscape and its land use are analyzed (Bockstael, 1996, Werner and Bork, 1998). To accomplish this goal, most landscape or land-use models distinguish different processes in the landscape and describe relevant components separately. For the abiotic components, many models or sub-models exist for the local or the regional perspective (e.g., Addiscott and Mirza, 1998; Bass et al. 1998; Dunn et al., 1996). Only a few models are available now that try to assess the impact of land use on biotic components, species, or their habitats (e.g., Schultz and Wieland, 1995; Lutze et al., 1999). A crucial point in using complex land-use models is the availability of data that describe the specific region in terms of the site conditions, the actual land-use structure and the noncultural biotopes of a landscape (Briassoulis, 2001). When assessing the impact of land-use changes for a large area, in most cases only data with a low level of spatial detail are available for site conditions, noncultural biotopes or structure of the land-use business. To collect data of actual land use, remote sensing can very easily provide a set of data that can cover completely the entire region (Wadsworth and Downey, 1996). Other data, especially those for actual management, are generally available with a high level of detail only for selected farms or other land-use businesses. In most cases, only data sets without a detailed spatial resolution are available as statistical data for an entire region. Approaches of Modeling Land Use and the Effects of Land Use After indicators to be addressed have been defined (Moxey et al., 1998), models are selected or developed that describe explicitly the processes or relate the values of the indicators to the specific land-use situation (e.g., Johnes, 1996). All these different models should be linked either physically within a software-framework (Dunn et al., 1996, Lutze et al., 2000, Tufford et al., 1998) or run separately, exchanging data and information among single models (Wurbs et al., 1999). Concepts for Landscape Models With such simulation models, the analysis of landscapes will become an integral part of designing sustainable land-use systems and supporting the decision-making

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processes for regions or rural areas (Belcher and Boehm, 1998). The different concepts for designing landscape models can, according to Lutze et al. (2000), be distinguished into two groups: • Integrated models — All relevant processes are described with linked equations or algorithms; the entire model is developed in one set, and all parts must fit to each other from the internal logic and structure of the model as well as from the software development. • Modular models — All relevant processes are modeled separately in different modules, which are linked by software calls; this approach allows different internal concepts for the submodels and even different programming languages.

Depending on the perspective on the landscape, it is possible to distinguish between different model types (Antrop, 2000) according to approach followed: • Thematic approach — All relevant landscape components or compartments are described with the model and can be analyzed with regard to the effects of land use. • Regional or spatial approach — The landscape is divided into hierarchical units that are described separately with the model and can be analyzed with regard to the effects of land use.

Modeling Spatial Aspects Modeling the spatial aspects of interacting processes and driving forces is still a challenge for landscape modeling. In most cases, one-dimensional models (the dimension of time may always be added) are used to determine the impact of different land-use systems for defined points or homogeneous areas within the landscape (e.g., Kersebaum et al., 1995; Priya and Shibasaki, 2001; Wegehenkel 1999). These points or land units are selected from the entire landscape, so that (1) they are representative of a surrounding part of the landscape (in doing so, this piece of landscape is thought to be homologous for the relevant landscape properties; Verburg et al., 1999) or (2) sometimes the landscape is divided into cells of the same or different sizes, providing a full cover of the landscape with a grid (for each grid cell the one-dimensional model will be calculated; Børgesen et al., 2001). In both approaches, sometimes not all possible points or cells within a landscape are simulated; only a selected number of typical combinations of sites and land use are defined and simulated. Stepwise models are also developed that take lateral processes into account or are valid for a complete portion of the space in the landscape. This modeling is mainly for water and matter flow (e.g., Ilyas and Effendy, 1996, Johnes and Heathwaite, 1997). Modeling biotic components and processes that are related to organisms requires spatial-explicit approaches. Only a few models are available that deal with lateral processes for the biocoenoses of landscapes (Lutze et al. 1999). When developing landscape models with a spatial reference, it is necessary to define on which level of spatial detail (scale) the landscape should be analyzed (Bockstael, 1996). Processes within the landscape that imply the same components

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(e.g., water-dynamic) can have different spatial pattern on different scales (Wenkel and Schultz, 1999). Applying Models for Optimization of Land Use In many cases of decision making for rural areas, it is necessary to provide suggestions that help find solutions for the specific problem. In order to enhance a goal-oriented selection of land-use combinations or land-use systems, models are applied with optimization procedures (e.g., Keith et al., 1999). Zander and Kächele (1999) developed a complex model that allows estimation of the situation of predefined farms within large regions under different economic conditions. The model also includes estimations for ecological indicators for all possible combinations of crop management. With such an approach, simultaneous economic and ecological evaluations are possible. With a given set of preferences, the best feasible combination of ecological objectives and economic constraints can be found for a region (Meyer-Aurich et al., 1998).

DECISION MAKING FOR LAND-USE PLANNING IN RURAL AREAS THROUGH MULTI-OBJECTIVE OPTIMIZATION — AN EXAMPLE Decision making in rural planning, as within other complex systems, requires having (1) different options, (2) sufficient information about these options, and (3) the power and other necessary resources to put a decision into action (Steffen and Born, 1987). Rural planning comprises agriculture, forestry, fishery, tourism, and infrastructure, among other areas. Simulation and ecological optimization of the management of each of these sectors requires specific models. Because agriculture dominates rural areas, assessing the impact of such land use is most relevant in analyzing the environmental threats of changing land-use systems for rural areas. Modeling agricultural decision making under consideration of ecological objectives is the focus of this section. The classical decision-making process in agricultural land use is related to mainly one goal: maximizing the economic profit of the farm. Often stability of income as well as cash flow are defined as economic goals. Introducing additional goals, such as environmental objectives or those of nature protection, to the decision making of the agricultural business leads to a more complex situation. It is then necessary to optimize the activities and the production process toward more than a single goal (maximum economic output). Now selection of appropriate measures in land use must be done with several goals in mind. However, it is barely possible to maximize the outcome of all objectives simultaneously. In most cases, a compromise among several objectives is the best possible solution, and only a few (if any) of the goals can be fully realized; In order to find the best solutions, or compromises, a multiobjective optimization process is necessary (Alocilja and Ritchie 1990). To support the decision makers whose goal is environmental protection (i.e., abiotic- and biotic-oriented goals), it is necessary to supply them with land-use

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Table 12.1 Priorities for Environmental Quality Goals Specific for Single Fields (Principle Pattern, Examples)

+ ++ ++ ++ ++

+ + ++ R R

R R R ++ ++

R R R ++ ++

++ ++ ++ ++ ++

++ ++ ++ ++ ++

Cranes

+ R + R ++

Amphibia

+ + + ++ ++

Barn Owl

+ + R ++ ++

Gray Bunting

1 2 3 4 5

Partridge

Field-no. (example)

Goals Related to Single Species

Biotopes, Protected

Protection of Ground Water Ground Water-Recharge Preventing Wind Erosion Preventing Water Erosion Valuable Ponds Oligotrophic Biocoenoses Dry Meadows Valuable Biotopes Ruderal Vegetation

Abiotic Goals

+ + R + +

R + – + R

(+) (+) (+) (+) (+)

– R ++ R R

– + + + –

Relevance of the distinct goal for the corresponding areal unit: ++ = very important, + = important, R = rare, – = irrelevant, (+) = important if species does occur. Source: Adapted from Plachter and Korbun (2001).

alternatives that can be considered in order to achieve the desired ecological goals. The decision makers on the production side need information about the effects these different land-use options have on the economy and the structure of the farms. The representatives for environmental protection in this decision-making process need information about the ecological impacts that would be caused by some specific options of the agricultural production systems. Representatives of both the farmers and those for the environmental protection need to consider the best solution for both sides. The Multi-Optimization Model The predefined cropping practices (Table 12.1) and their economic as well as their ecological effects (Figure 12.2) are a partial evaluation information of the crop management systems and the base for a complex simulation model (Figure 12.3) (Zander and Kächele, 1999). With this model one can find the most suitable combination of crop production systems for a given farm situation or region according to predefined ecological and economic goals. The search steps in MODAM are performed through a farm model by optimizing total gross margin with ecological objectives as restrictions (multi-objective-optimization). A series of consecutive runs of the model is conducted. In each run, the model is forced to use a 10% higher achievement rate for one specific environmental goal, going from the chosen reference situation and to 100% in the achievement of the goal (Figures 12.4 and 12.5). The resulting relationships between the economic and the ecological variables are represented in trade-off functions. With the MODAM system several optimal economic-ecological solutions for given objective functions can be found. It is also possible to analyze the impact of

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degree of success

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1.0 0.8 0.6

winter-wheat

0.4

12#

0.2

degree of success

0.0 1.0 0.8

winter-rape

0.6

48#

0.4 0.2

degree of success

0.0 1.0 0.8 0.6

corn for silage 12#

0.4 0.2

Figure 12.2

environmental quality goals

cranes

amphibia

partridge

typical field weed-vegetation

low trophic habitats

small ponds in the fields

erosion: water

erosion: wind

ground water: recharge

groundwater: nitrate pollution

0.0

Distribution characteristics (box plots) in the success of environmental quality goals with different crop production systems for winter-wheat, winter-rape, and corn for silage. (Estimations for 192, 48, 132 standardized crop production systems, including four different soil fertility classes; production region: northeast German hill area; derived by estimating algorithms from Meyer-Aurich et al. (1998) in the multi-objective decision-making tool MODAM.)

predefined economic (agro-political) conditions on the developing land-use situation and its impact on selected environmental quality goals. In the research study the environmental quality goals were defined by ecologists specifically for each single field within the study area. These goals were given as priorities that should be fulfilled (Table 12.1).

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site characterization

goals production practices from expert knowledge

partial economic evaluation

partial ecological evaluation

socio-economic conditions

farm resources

multiple goal linear programming model

regional sector model

economic overall evaluation

Figure 12.3

regional land use pattern

trade-off, scenarios, interactive simulations

ecological overall evaluation

Iterative definition of goals and evaluation of the possibilities of their success with the modules of MODAM. (From Zander and Kächele, 1999.)

risk of nitrogen leaching wind erosion ponds weed flora amphibian

groundwater recharge water erosion oligotrophic biocoenosis partridge

100% goal achievement on agricultural land

80% 60% 40% 20% 0% -20% -40%

80%

85%

90% total gross margin

95%

100%

-60% Figure 12.4

Trade-off between the reduction of nitrate leaching and the gross margin of the mixed farm in the research area Wilmersdorf for selected environmental quality goals. Results from simulation studies with MODAM for an area of 1.821 ha in the southern Uckermark, Brandenburg, Germany. (From Zander, 1998.)

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risk of nitrogen leaching wind erosion ponds weed flora amphibian

289

groundwater recharge water erosion oligotrophic biocoenosis partridge

100%

goal achievement on agricultural land

80% 60% 40% 20% 0% -20%

80%

85%

-40%

90%

95%

100%

total gross margin

-60%

Figure 12.5

Trade-off between the reduction of nitrate leaching and the gross margin of the cash crop farm in the research area Wilmersdorf for selected environmental quality goals. Results from simulation studies with MODAM for an area of 1.821 ha in the southern Uckermark, Brandenburg, Germany. (From Zander, 1998.)

Simulations for the Study Area For the study area, the environmental goals were available for each single field (see above section). These goals were given highest priorities (Table 12.1). When applying the MODAM system to these predefined goals, several solutions, fulfilling the goals to different extents, can be found. It is possible to have substantial achievement in some environmental goals without losing too much gross margin for the farmers. For the mixed farm (Figure 12.4), it is possible to reduce nitrate leaching up to 85% by a 4% reduction in the gross margin (100% is the reference situation: integrated farming). This reduction is achieved by selecting cropping systems that will have the respective reduction of nitrate leaching. As with all situations in real life when several goals should be reached at the same time, it is rarely possible that all goals can be fulfilled with the same approach. Therefore, the possible solutions concerning the given set of environmental quality goals for the analyzed region show different degrees in fulfilling the expected goals (Figures 12.4 and 12.5). In addition, some environmental goals are congruent (their goal achievement heads in the same direction when cropping practices are changed). As can be seen in Figure 12.4, when a reduction in nitrate leaching occurs by switching cropping practices, a relevant reduction in the impact on oligotrophic biocoenoses and on weed flora also occur, although the level of achievement is less than that in the reduction of nitrate leaching. However, some goals can be divergent in their reaction to changing cropping practices. While it is possible to have a reduction of nitrate

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leaching in the mixed farm through adapted cropping practices, the resultant situation for amphibians is worse (Figure 12.4). There is, to some extent, a greater possibility to enhance the positive effects of environmental quality goals in the mixed farm than in the arable farm (Figure 12.4 and 12.5). In the mixed farm, achievement of most goals is higher with the same loss of gross margin than in the arable farm. One reason for this difference is the already good (to an extent) environmental situation of the arable farming system in the reference situation (integrated farming). Another reason is the greater ability in a mixed farm to introduce ley or other crops that cover the soil surface year round and provide soil protection as well as food and shelter for some species (cattle production needs fodder, for example, by ley crops). This complex information can help find those solutions that can still be accepted by the conservationists, from an ecological point of view, and by the farmers from an economic point of view. Sometimes the achieved environmental or economic situation will not be satisfying for the decision makers. In such cases it would be necessary to check if the predefined goals should be kept, altered, or even replaced by others. An iterative process will then start: defining goals, estimating the economic and ecological impacts, redefining goals, estimating the economic and ecological impacts, etc. The developed method also can help define the necessary additional compensation that would be necessary to encourage the farmer to adopt the cropping practices that would lead to attaining a set of environmental quality goals. This compensation payment could come from groups that have interest in achieving the nonbusiness goals of the farmers (private organization in environmental protection, nature conservation, or society in general). Also, the appropriate compensation could be derived with the described method when farmers would be forced to attain the desired environmental quality. In the process of finding suitable cropping systems for sustainable land-use development, it is necessary to have alternatives for the joint and participatory decision-making process. For the study area, two possible priorities (abiotic and biotic) were given as an example. With the MODAM tool possible land-use solutions were found (Figure 12.6). When a primarily abiotic set of goals is given, the resulting cropping practices can enhance the achievement of the abiotic goals by up to 20% (limited by too high economic losses with higher achievement levels). But a 6% or 11% loss in gross margin for the farm would result, depending on the farm structure (Figure 12.6). Greater losses in gross margin would occur when primarily biotic goals would be followed (Figure 12.6). An Outlook with Scenario Studies of Agricultural Politics The agricultural politics of the European Union are in transition, and agropolitical conditions are not yet defined. Several scenarios suggest drastic changes in the subsidy system. The current system of subsidized farming could be altered to a world market situation without additional public payment for farms or their products. For planning purposes on the level of politics, farms, and the administration of

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changes in the

goal achievement (%)

30 25

priority:

20

abiotic resource protection

15 10 5 0 -5

in arg gro ss m

sma

olig

n

ion

er e wat

win

ros

osio d er

er r wat

und gro

nitr

ate

leac

hin

ec

-15

ll po n ds otro ph. coe sge tal f lora par trid ge amp hibi a

-10

cash crop farm

abiotic biotic environmental quality goals

crop and animal farm

changes in the

goal achievement (%)

30 25 20

priority:

15

biotic resource protection

10 5 0 -5 -10

abiotic biotic environmental quality goals

Figure 12.6

in arg gro ss m

sma

ll po nds olig otro ph. coe sge tal f lora par trid ge amp hibi a

n

ion ros

wat

er e

osio d er

win

er r wat

und gro

nitr

ate

leac

hin

ec

-15

Success of selected environmental quality goals and the gross margin of simulated farms (cash crop and mixed farm) in the research area Wilmersdorf with setting priorities on either primarily abiotic (top) or biotic (bottom) goals when looking for economically and ecologically optimized crop production. Results from simulation studies with MODAM for an area of 1.821 ha in the southern Uckermark, Brandenburg, Germany. (From Zander, 1998.)

environmental and nature protection, it is necessary to estimate the economic and ecological effects from such possible change in conditions. For determining the effects of changing conditions, the possible futures in the agropolitics of the European Union were analyzed. Five developments in subsidizing agriculture were assumed: (1) no subsidies (free trade and world market prices for agricultural products); (2) subsidies per land use area and involved labour (subsidies

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per ha of arable land and per number of employed persons for farming); (3) subsidies per land use area (subsidies per ha, amount dependent on regional yield level); (4) subsidies for protection of abiotic resourcesand (limitation of nitrogen supply dependent on the site specific yield potential); (5) continuation of the current system (subsidies only for specific crops and per ha of arable land). By applying the MODAM system, the land-use situation that can be expected under specific conditions was estimated for a region of about 1.800 ha. The pattern of crops in a 6-year rotation and the economic optimal management practices on each field in the region were analyzed for the effects on selected abiotic goals, on selected species, and on habitat quality. The ecological analysis was done by using the estimation procedures from Meyer-Aurich et al. (1998). Economic conditions served the possible future agropolitical programs that currently are discussed as future political options. These five scenarios were analyzed in their impact on four abiotic goals, three goals of habitat protection, and three goals of species protection. In the simulation, two different farming systems were assumed: a farm solely based on arable crop production and a farm with mixed crop and animal production. Figures 12.7A and 12.7B show the results as changes in the achievements of the respective ecological goals with the reference situation as base. In an arable farming system, all scenarios will produce a reduction in the achievements of ecological goals (Figure 12.7A) mainly because of reduced set-aside fields and the resulting loss in those crops that have permanent, or at least year-round, vegetation. In mixed farming systems, the possible economic conditions would lead to cropping systems that reduce mainly the impact on ponds and reduce soil erosion by water or wind (Figure 12.7B); an improvement in the ecological quality goals will take place. Reduced attainment of all other environmental quality goals, will also occur under the given scenarios. Consequently, all discussed economic conditions within the coming European Union agropolitics would deteriorate the environmental conditions in agriculturally used landscapes compared to the current situation. Perspective The participatory and iterative procedure was developed for the northeastern arable region in Germany. An adaptation to other sites and regions is easily possible. In order to make such an adaptation, the regional environmental quality goals have to be determined, the yield expectations (site-specific potentials) have to be estimated, and the sets of different production technologies (e.g., cropping practices) have to be defined. The latter can be done using local expert judgment. The described procedure has to be developed continuously in the future. The MODAM system does not yet include the evaluation of nonagriculturally used areas in a region. Especially to determine the impact of land use on habitats and specific species, it is necessary to look beyond the fields and grassland. It is also important to analyze the structure of the landscape and the interactions between the agriculturally used area and those components of the landscape that are left for nature. New methods for goal definition as well as new evaluation tools have to be developed. Such additions to MODAM are in preparation.

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A. Scenario no subsidies crane amphibians

subsidy per area and labor

partridge ponds water erosion

subsidy per area

wind erosion groundwater recharge nitrate

abiotic resource protection

reference situation

-25%

-20% -15% -10% -5% 0% Change in target value in % of reference situation

5%

B. Scenario no subsidies crane amphibians partridge

subsidy per area and labor

ponds water erosion

subsidy per area

wind erosion groundwater recharge nitrate

abiotic resource protection

reference situation

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

Change in target value in % of reference situation

Figure 12.7

Variation in the success of environmental quality goals caused by the impact of different land use situations due to four possible different agro-political conditions in the future European Union agropolitics. Results from simulation studies with MODAM for an area of 1.821 ha in the southern Uckermark, Brandenburg, Germany; ref. sit. = simul. results with conditions of the European Union agropolitics as in 1998 (Meyer-Aurich 2001). (A) Situation in an arable farm. (B) Situation in a mixed (animal and crop production) enterprise.

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ACKNOWLEDGMENTS The research activities upon which this chapter is based were made possible through basic funding by the state Ministry of Agriculture, Environment and Spatial Planning of Brandenburg (Potsdam) as well by the federal Ministry of Consumer Protection, Nutrition and Agriculture of Germany (Bonn).

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CHAPTER

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Ecological Guidelines for the Management of Afforestations in Rural Areas Stanis l aw Ba l azy

CONTENTS Introduction............................................................................................................299 Shelterbelts and Woodlots in the Structure of Biogeochemical Barriers.............301 Principles of Mid-Field Afforestation Management .............................................304 Conclusions............................................................................................................311 References..............................................................................................................312

INTRODUCTION The widespread transformations of natural landscapes reflect thousands of years of human impact on natural ecosystems. Pastures, cultivated fields, plantations, villages, towns, industrial complexes, and huge metropolies replaced forests, grasslands, and swamps. Removal of permanent plant cover resulted in intensification of water and wind erosion, higher leaching rates of chemical compounds into underground and surface water reservoirs, impoverishment of biological diversity, and other deteriorations of the biosphere. In areas dominated by arable fields, protective functions against destructive climatic effects on settlements, livestock, and plants were performed by the remaining afforestation fragments and bushes. Their protective role has long been recognized and appreciated, and is best witnessed by the continuously supported networks of shelterbelts and hedgerows in the European countries along the Atlantic coast, beginning with the western edges of Scandinavia through the British Isles, down to

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the northwestern parts of France (Meynier 1976, Pape 1976, Stanners and Bourdeau 1995, J. P. Marchand, personal communication). Until now, these structures were mainly composed of native plant species, despite growing tendencies to introduce foreign tree and shrub species in the reafforestation of areas excluded from agricultural production (Hooper 1976, Delelis-Dusollier 1986, Alexander et al. 1986). For similar reasons, the hedgerows are permanently maintained on agriculturally utilized areas in mountains and uplands of strongly diversified relief along the wide central European belt from Cantabrian to the Carpatian Mountains. In the Council of Europe paper, Biber (1988) used the French term bocage for this kind of afforestation. Stanners and Bourdeau (1995) called them semi-bocage, whereas in the majority of papers the terms haies, shelterbelts, hedgerows and windbreaks were commonly used as synonyms. As early as the 1820s Ch l apowski (1835) introduced and recommended midfield afforestation systems in the Wielkopolska region of Poland modeled on English hedgerow patterns, pointing out a number of their advantageous effects for agriculture. He considered the most important benefits to be timber, forest fruits, herbs and honey, protection of fields and cattle against wind, and elimination of shepherd employment on pastures surrounded with thorny hedgerows, which simultaneously provided shade for animals. Among tree species particularly useful in shelterbelts Ch l apowski recommended the black locust (Robinia pseudoacacia) and among shrubs he recommended the hawthorns (Crataegus monogyna and C. oxyacantha), but he also planted more than 20 species — including some exotic ones, such as honey locust (Gleditschia triacanthos) and catalpa (C. bignonioides). Ch l apowski also stressed the role of shelterbelts for their scenic values and their shaping of field contours. As an educated military officer and participant in the Napoleonic campaigns, Ch l apowski also appreciated their military significance. The afforestations that he had established on an area of about 10,000 ha survived both World Wars and gave rise to a largescale research program started in the 1950s by the Research Centre for Agricultural and Forest Environment of the Polish Academy of Sciences in Poznan´ (RCAFE). In forest-steppe and steppe areas of southwestern Russia, strongly deforested in the 18th and 19th centuries, the local population started to plant the edges of fields and settlements with afforestations to counteract damages caused by dry winds and soil erosion (Sobolev 1948, Petrov and Skachkov 1987). The farmland abandonment in the set-aside program recently proposed by the Common Agricultural Policy of the European Union produced a new problem of management of areas permanently or temporarily excluded from tillage. It coincided with the recognition of new environmental threats, such as water shortages and water contamination, caused by intensified plant production, large-scale livestock farming, and industrial emissions. A simultaneous strong decline of biological resources in farmland has been ascertained. It became necessary to counteract diffuse pollution of soils and waters, to stimulate water retention in regions of low precipitation, to widen application of nonchemical pest control means, and to augment the maintenance and restoration of wildlife resources in agricultural landscapes. Among the various possibilities for set-aside field assignments, proposals have been accepted for total or partial reafforestation of the fields — including agro-forestry utilization systems, shelterbelt planting, and natural succession — as well as creation of refuge

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habitats for rare or endangered species protection and other forms of management supporting nature conservancy.

SHELTERBELTS AND WOODLOTS IN THE STRUCTURE OF BIOGEOCHEMICAL BARRIERS Studies on the limitation of environmentally harmful side effects of intensive farming, carried out over many years as part of a broad research program on energy flow and matter cycling in agricultural landscapes (Ryszkowski 1975, Ryszkowski and Bartoszewicz 1987, Ryszkowski et al. 1997, 1999, Prusinkiewicz et al. 1996, Ke˛ dziora and Olejnik 1996) confirmed the pertinence of biogeochemical barriers elaborated by Ryszkowski and co-workers (1990). Under the moderate climatic conditions of Europe, the main structural landscape elements of such barriers are mid-field woodlots, shelterbelts, wetlands, communities of perennial vegetation, and open (surface) water networks. The following processes determine the functions of biogeochemical barriers: • The kind of vegetation cover modifies solar energy fluxes used for evapotranspiration, soil, and air heating, thus influencing water circulation and biochemical reaction intensity, as well as local air mass movement (wind, heat advection, and convection processes) (Ryszkowski and Ke˛ dziora 1987, Ke˛ dziora 1996, Ke˛ dziora and Olejnik 1996). Plant cover structure also determines the potential for wildlife survival (Karg and Ryszkowski 1996, Ryszkowski et al. 1999). • The main methods of matter cycling in agricultural landscapes are migration by underground and open waters, transportation by air movements, and transformations brought about by living organisms (primary production, decomposition, mineralization and migrations — Ryszkowski et al. 1990). • Spatial structure of the plant cover modifying speed and direction of air masses also influences airborne pollution. Chemistry of ground and surface water is controlled by vegetation and animal migrations.

More than 20 different functions favorable to the environment, human economy, health, and culture have been listed in papers concerning the role of shelterbelts and woodlots (Zaja˛ czkowski 1997). One can distinguish, however, the following more general categories of function that should be considered the most important for agricultural landscapes: • Increase of water retention by the restricting surface runoff and drying effect of wind • Purification of ground waters and counteraction of nonpoint pollution spread in the landscape • Prevention and restriction of wind and water erosion effects • Mitigation of effects of unfavorable climatic phenomena (extreme temperatures, long-lasting droughts, storms, etc.) • Isolation of polluting elements in the landscape (dumping sites, industrial areas, animal farms, etc.) • Preservation of biological diversity in agricultural areas and stimulation of pest control efficiency

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Water protection, both of its resources and purity, is the paramount problem for most regions. Afforestations affect water retention because of the greater water storage capacity of their litter and soil than that in arable fields. Plant cover increases infiltration rates by slowing runoff. These phenomena, including soil penetration by tree and shrub roots which enables deeper percolation through impermeable layers of loess or argillaceous soil profiles, were recognized before the end of the 19th century. This recognition provided some theoretical basis for regional reafforestation programs aimed primarily to ameliorate soil humidity conditions and to restrict erosion in steppes or deforested agricultural areas. Such efforts started during the first half of the 20th century in the chernozem areas of Ukraine and the European part of Russia, and then broadened to include some Asiatic parts of the former Soviet Union (Sobolev 1948, Gorshenin 1949, Aderichin et al. 1983, Lamin 1983, Petrov and Skachkov 1987). Shelterbelt networks further augment water retention because they reduce wind velocity that would otherwise diminish evapotranspiration from the fields. Moreover, recent meteorological studies have shown that the indices of horizontal precipitation (dew, fog) are greater in densely afforested fields than in open ones (Ke˛ dziora 1993). According to estimates by Ryszkowski and Ke˛ dziora (1987, 1993), water deficits in rural areas may be reduced by 40 to 60 mm by wellmanaged shelterbelt networks, which is especially important in low precipitation seasons. Beneficial effects of afforestations on water purity result from phytosorption of chemical compounds from the soil solution. However, the trees have a greater ability to intercept these compounds than do herbaceous plants because of the extensive root systems and significantly greater evapotranspiration by aboveground structures. Moreover, some amount of contaminants is subjected to additional transformation by the floor vegetation and the superficial layer of soil and litter, whereas a considerable part of absorbed chemical compounds remains immobilized for dozens or hundreds of years in accumulated timber biomass. They may be released from local cycling after burning or microbiological decay. In view of the growing problems of nonpoint pollution control, these processes, overviewed historically by Correll (1997), have become extraordinarily important for intensive agriculture areas. Investigations of water purification efficiency in the Central Povolzhe chernozem region of Russia by the 12.5-m wide deciduous shelterbelts (composed of 40% birch, oak, and linden and 60% maple) showed that pollution was reduced 20–30% in the case of shelterbelts alone compared with open fields, and by over 50% in the case of shelterbelts with an embanked ditch (Antonov 1987). Fertilizers not absorbed by cultivated plants in the shelterbelt-only decreased 9 to 42.5% and herbicides decreased 91.4%, whereas for the shelterbelt with embanked ditch the reductions were 44.5 to 76.3 and 96%, respectively. Detailed studies in RCAFE (Ryszkowski 1987, Ryszkowski and Bartoszewicz 1987, Ryszkowski et al. 1997, 1999) showed strong dependence of efficiency not only on shelterbelt width, but also on water flux intensity, soil permeability, meteorological and weather condition changes, and the type and quantity of organic matter accumulated under the canopy. Despite relatively great variability of chemical concentrations in particular samples, a statistically significant decline in nitrates and some cations has been assessed in ground water under shelterbelts of an experimental 10,135-ha watershed. The mean annual amount

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of nitrogen leached from sub-watershed covered 28% by biogeochemical barriers (forests, shelterbelts, meadows, and wetlands) was only 1.5 kg/ha, whereas other areas practically devoid of such barriers (99% of arable fields) had 20.4 kg/ha. Trees have long been widely applied as anti-erosive measures on arable fields. Their rather obvious suitability for this purpose results from relatively great height and flexibility of stems and branches as well as deep and strong root systems that anchor in the soil. These root systems together with the roots of plants growing under the canopy form a dense stabilizing network resistant to erosion. In order to prevent water erosion processes, the application of arborescent plants must be combined with other, often rather complicated, protective activities, especially in mountain and upland regions of diversified relief. Methods for counteracting different kinds of erosion have been described and are currently being improved (Instruction 1952, Sobolev 1948, Tibke 1988, Ticknor 1988), but it would be difficult to imagine effective erosion control without arborescent plants as part of the complex of preventive measures. Afforestations are able to counteract or minimize the effects of extreme climatic or weather phenomena (particularly low and high temperatures, droughts, and storms) that have a detrimental influence on plant cultures, open animal breedings, living conditions, and human health; for example, they have an obvious anti-erosive function. The peri-Atlantic region hedgerows (mentioned above) and numerous other naturally woodless or otherwise deforested areas have been protected mostly for these reasons. Different and often expensive efforts aiming at reafforestation of such areas have been undertaken in many regions. Among a wide range of problems that it addresses, the activity of the Canadian Prairie Farm Rehabilitation Administration, Shelterbelt Centre (PFRA) is directed at the management of hedgerow systems in woodless North American areas, especially those with a relatively humid climate and severe winters (Schroeder 1988). It cooperates with some divisions of the USDA and with scientific and experimental institutions of Russia, where similar conditions dominate great areas (Lamin 1983, Gabeev 1983, Stadnik 1984). Annual reports of the Shelterbelt Centre, published by the PFRA, contain useful information on progress in nursery techniques, results of scientific research, establishment of shelterbelts, pest and disease protection in afforestations, improvement of planted tree value, and use of their resources for human needs and environmental protection. A diverse range of activities linked with tree or shrub planting is applied in arid zones for the protection of soil humidity and to increase soil fertility (e.g., by mulching with bush twigs), counteract torrid heat, shade pastures, and improve living conditions of livestock. Recently, dense shelterbelts with rich bushy undergrowth have been planted on some Polish farms aimed at qualified seed production, in order to restrict the possibility of undesired cross pollination between cultivars (Ba l azy et al. 1988). Because afforestations have a strong buffer capacity to ease threats caused by climatic factors and chemical pollutions, they are widely applied in spatial management. They are planted along borders between industrial and inhabited parts of agglomerations and to isolate other burdensome areas (e.g., dumping grounds, animal farms, highways); they are also planted around health and convalescent centers, resorts, and other locations to beautify grounds and landscapes.

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All types of afforestations favor wildlife resource preservation in agricultural landscapes and maintenance of rich biodiversity. Until the past few decades, agricultural areas were regarded as having little significance for nature protection because of the well-known destructive effects of tillage and agricultural chemicals. However, investigations of ecological effects of intensive agriculture, carried out by the RCAFE as part of broad programs, showed that in the differentiated landscape structure of arable fields, abounding in small nonproductive natural elements (woodlots, bushes, wetlands, seminatural plant associations, water bodies, and others), the richness and diversity of living organisms are comparable to those of other nonutilized ecosystems. This point of view was expressed in the Polish strategy of biological resource protection (Ryszkowski and Ba l azy 1991) and later accepted as a general guideline of the European Community landscape and biological diversity protection Biological and Landscape Diversity Strategy (Pan-European strategy 1996, Ryszkowski et al. 1996). Thus, biogeochemical barriers enable landscapes to diminish loads and to restrict dispersal of diffuse (nonpoint) pollution, transforming them by biochemical processes into gaseous emissions, absorption by soil-inhabiting biota, and accumulation in timber biomass and organic deposits. The patches and strips covered by woody plants usually form basic networks for biogeochemical barriers that • reduce various forms of soil erosion and improve solar energy partitioning, water regime and local agroclimatic conditions because of biological structure of trees • stimulate self-purification processes because of networks of roots, under-canopy vegetation, and organic deposits • protect rich associations of biota due to persistent, multi-storied habitats, functioning as refuges and horizontal corridors

Apart from the functions listed, afforestations significantly augment aesthetic and recreational landscape values, often inspiring artists, and are subjects of ecological education and scientific research. They simultaneously produce a range of directly utilizable goods, such as wood, honey, fruits, mushrooms, and pharmacological plants, and improve habitats for game. Hence, they are always multifunctional elements in any landscape structure. Their efficiency has been determined mostly by the types, share, distribution in the landscape, species composition, and state of management (i.e., quality). All those elements should be considered when new shelterbelts or their functional networks are laid out.

PRINCIPLES OF MID-FIELD AFFORESTATION MANAGEMENT Past efforts to protect or introduce shelterbelts that embraced ecological premises aimed to improve environmental conditions either because of hazards resulting from a high degree of landscape deforestation (as in the case of bocages) or because of expected benefits from amelioration of some environmental factors influencing agricultural production (e.g., increase of soil humidity and erosion control in east European steppe chernozems, relative stabilization of water regime in hydrogenic lowland soils exposed to bogginess in the Lombardian Lowland of Italy or at the

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· Vistula River outlet in Zu l awy of Poland, planting of fast-growing trees in riparian sites of the Hannovermünde area in Germany). The recent progress in agro-ecological research made it possible to predict relatively accurately the impact of shelterbelts on agricultural environments. Afforestation problems have usually been underestimated in comparison to other factors determining socioeconomic development of rural areas. Their importance depends largely on climatic conditions, relief, and land-use structure, as well as on applied tillage systems, general level of agriculture development, environmental hazard intensity, and material resources of the society. The last factor most fully determines the possibilities and extent of environmental protection programs that also involve afforestation tasks. After the period of political, social, and economic changes in central and east European countries in the 1980s, programs for agricultural landscape protection and management were developed for Hungary, Poland, the Czech and Slovak Republics, Lithuania, and the Ukraine (Ba l azy and Ryszkowski 1999). Only in the first three of these countries was the income per person greater than $5000 USD, an amount, according to some economists, below which efficient citizen participation in costs of environmental protection is impossible. For steppe areas of Moldova, the Ukraine, and Russia, antierosive and water-protection programs of afforestations were not realized until the 1980s. It seems that despite proprietary, structural, and administrative changes in the agriculture of countries of the former Soviet Union, these programs will continue to be developed and implemented because of the highly significant impact of windbreak networks on crop yields in the chernozem soil regions. In the early 1980s, a modification of the principles for agricultural land use in the Ukraine was presented (Tarariko 1992a, 1992b, Medvedev and Soko l ovaki 1992). It aims at regionalizing row and cereal crops on soils in two situations with erosive hazards because of slope inclinations 0 to 3° and 3 to 7°. The third soils group with sloping over 7° would not be subjected to cultivation except for sustaining grassland cover or reafforestation. To obtain a relative balance of the factors destabilizing and stabilizing landscape resistance, it would be necessary to introduce approximately 50,000 ha of forest and shelterbelts in the forest zone, 500,000 ha in the forest-steppe zone, and 750,000 ha in the steppe zone, independent of a range of other changes in the land-use structure and agrotechnologies implemented thus far. The Hungarian and south Romanian plains are very similar to east European forest-steppe areas and are threatened by the same processes although of a slightly lower intensity because of a more favorable seasonal distribution of yearly precipitation. However, reafforestation or shelterbelt planting programs may be difficult to introduce, especially in Romania, because of denationalization of large state and cooperative farms that were divided among countryside inhabitants as individual or family farms (Von Hirschhausen et al. 1999). The creation of rationally functioning networks of shelterbelts under conditions of a highly fragmented estate is very difficult because of the necessity to obtain the owners’ agreement. Moreover, both the already existing and newly planted afforestations are exposed to greater damages from inhabitants because of their deep conviction about significantly competitive capabilities of trees against cultivated plants. Indeed, some decrease in development and yield of crops has been observed along a narrow strip adjacent to the afforestation

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border. However, Kort’s (1988) review on worldwide references concerning the effects of shelterbelts on different crop yields showed only three instances of crop output decline out of the 97 considered. Two of them were large oats fields and the third was spring wheat in a field strip located leeward of a shelterbelt. In 93 cases, the yield increase was 3 to 35% for most cereal crops and 65% for millet, and 70% to over 100% for hay and some papilionaceous perennial crops (in one case of alfalfa the increase was 203%). As a result of this analysis, the author concluded that yield increase from shelterbelt was usually more conspicuous in drier regions. Some tree or shrub species inappropriately included in shelterbelts may stimulate appearance of pest insects, mostly aphids (Voegtlin et al. 1988) or plant diseases caused particularly by rust fungi or viruses (Ba l azy 1997b). However, such undesirable phenomena may be easily eliminated or reduced by careful selection of species, appropriate spatial distribution, and intervention in shelterbelt managements, such as crown shapening, root pruning, and opening of shelterwoods. Positive effects of rationally managed mid-field afforestations always prevail over the negative, even though they are not conspicuously reflected in yields (Kort 1988, Knauer 1990, Fitzpatrick 1994, Ryszkowski et al. 2000). Despite the benefits of shelterbelts for the environment and their increasing implementation, often performed by specialized institutions, analyses of landscape structure frequently show a decreased afforestation in some countries. For example, the estimate of shelterbelts in England (Hooper 1984) showed that in the two decades after World War II approximately 70,000 km of hedgerows were removed either to augment arable areas or to install electrical supply lines. Mannion (1995) reported declines as high as 22% until the mid-1980s. French legal mandates of the 1940s regarding mergence of scattered fields caused great losses in the hedgerow networks of the northwestern part of this country (Baudry and Burel 1984, Augé 1999). The analysis of satellite pictures of different regions of France (Bras and Piveteau 1999) showed an approximately 1% annual decline in hedgerows, woodlots, and single trees in agricultural areas. In 1991–1996, the greatest decreases occurred in Calvados, the Brittany Peninsula, and the central parts of the Parisian Basin. A 1.3% increase in afforested areas was observed in only a few small but highly afforested districts mainly in the south and in the vicinity of Calais. Full or partial adjustment of the former DRG agriculture to EC standards would likely result in a decline of linear elements differentiating the landscape of arable fields (shelterbelts, balks, roadsides, etc.). Full adjustment would decrease those elements from 920 m/100 ha to 910 m/100 ha; partial adjustments would result in a decrease to 700 m/100 ha. However, a simultaneous increase of afforested areas would also occur, which should lengthen forest-field borders from 670 m to 720 m and 740 m, respectively (Stachow and Haberstock 1995). Estimations in recent decades show decreased shelterbelts in farmland in most regions of Poland (Zaja˛ czkowski 1996, Budzyn´ ski 1997). Since the mid-1970s, nurseries producing seedlings for mid-field afforestations decreased by about 2300 ha. In the same period, the number of tree seedlings planted yearly decreased approximately threefold and plantings of shrubs decreased eightfold. The tree felling increased primarily to remove mature roadside trees and woodlots, planted at the

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beginning of the 19th century, as well as poplar afforestations, planted in the 1950s as part of the country’s plan to augment timber resources. Felling afforestation trees to increase timber yields, which also occurred in other countries of eastern and central Europe, is connected with the impoverishment of the rural population because of the associated agricultural transformation processes (Hirschhausen et al. 1999, Ba l azy and Ryszkowski 1999). The degree of shelterbelt participation in the farmland of Poland varies greatly. Quantitative estimations carried out by the RCAFE in 33 districts along the country’s western border showed the differentiation range from about 100 m to 1500 m/100 ha and was usually similar in adjacent communes. In D. Ch l apowski Agroecological Landscape Park, which has a surface area of 17,200 ha and is considered to be one of the country’s best afforested agricultural areas, mean shelterbelt length/100 ha amounts to approximately 1740 m (Ryszkowski et al. 2000), whereas outside its borders, although in the same district, it amounts to 150 to 550 m/100 ha. In terms of the farmland afforestation program (Ryszkowski et al. 2000), the setaside areas should be qualified according to the following principle. When the total area of soil shows low fertility, large-scale reafforestation gains priority. In the case of a significant amount of good quality soils, the acreage with shelterbelt planting should predominate over reafforestated areas. However, local situations and individual landowners’ attitudes or intentions will considerably modify possibilities for both kinds of afforestations. The total area for the optimal variant of shelterbelt network to be planted in Poland was estimated at 350,000 ha, and for the minimum variant 250,000 ha. The most pressing needs occur in the central Polish lowlands with the greatest water deficits, an area of approximately 130,000 km2, and in the foothills and mountains of southern Poland that are severely or moderately threatened with erosion. Afforestations in rural areas should be designed and managed according to the following six guidelines. 1. Adjustment to the functions afforestations should perform in the environment Because afforestations are by nature multifunctional, one or more main functions should be ascribed to each of them. To fulfill that function they should be optimally situated and given proper species composition and tree-cover structure. It is therefore necessary to recognize the types and scale of environmental hazards significant for a given area and to assess which shelterbelt forms would most effectively counteract them. Afforestations perform a relatively full range of anticipated functions only if they form a rationally distributed spatial network. Thus it is absolutely necessary that they be harmoniously embedded into the structure of biogeochemical barriers, usually, and that embedding be, their most essential element. Water protection functions are most effectively performed by shelterbelts 10 to 20 m wide, the equivalent of three to seven tree rows. Since the interception of chemical substances from soil solution varies according to tree species, it is effective to plant biogroups composed of one, two, or three species. In order to obtain a dense filtering net in the total depth of soil profile, tree biogroups with deep and shallow root systems should be planted alternately. Deep and strongly rooting species (oaks, larch, sycamore, Scotch pine) should dominate in the outer rows to prevent damage from

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wind. It is advisable not to plant in outer rows those species with extending root systems, especially when they tend to produce sprouts (e.g., poplars). The belts should be localized transversally in relation to the direction of ground water flow, which in water-bearing layers is not always compatible with slope-surface angle. In agricultural landscapes with diversified structure, purification effects of shelterbelts and other elements of biogeochemical barriers are of basic significance for control of eutrophication processes in open water reservoirs. Multiyear monitoring of water contamination in the Agricultural Landscape Park in Turew showed, for example, that the spring content of nitrates, 45 mg/dm3, in ground waters under arable fields decreases to 2 to 5 mg/dm3 in waters outflowing to the drainage canal of the Park in a relatively dense and well-managed afforestation network. Two-row roadside afforestations of the allee type, if compact, well managed, and enriched with an under-canopy shrub layer, and distributed approximately along the contour lines of slopes, and distanced 400 to 600 m, may sufficiently reduce water contamination at a slope inclination up to 3%. With slopes of over 5%, afforested belts should be widened to 10 to 20 m and distributed alternately with strips of grasslands, arable fields, and berry-bearing shrub plantations in transversal arrangement. On excessively wet sites, increased use of trees that absorb large amounts of water for biomass unit production (birch, oaks, larch, poplars) is recommended to stimulate drying and purifying effects. The depth of the ground water table is an important determinant of shelterbelt significance because the purification effect may be insignificant if tree root systems do not reach the water-bearing horizon or at least the capillary soaking layer in the soil profile. In the protection zones of water intakes, as well as in the screening green around polluting landscape elements, the share of afforestations — together with compact forests — should be increased to 30% or even more. Typical wind-breaking shelterbelts should be rather narrow (one to three tree rows), not compact, and situated in general for Polish conditions, approximately north to south to break the predominant western wind, in distances of 350 to 500 m depending on soil and relief characteristics. Such structure, density could be attained in most cases by planting one or two tree rows along linear elements of farmland infrastructure (roadsides, ditches, streams, and other marginal patches). Species with shallow root-systems are of little value for these shelterbelts. Of course, the windbreaking function also is performed by all other forms of afforestations. Active landscape management for nature protection and biodiversity preservation requires maintenance and introduction of woodlots and bushes to function as wildlife refuges. They should be connected with greater areas of natural or seminatural ecosystems, such as marshes, peri-aquatic rushes, xerotermophilic bushy communities, greater afforested areas, and river valleys. Shelterbelts established or adapted for this purpose should generally be wider than the common wind-breaking strips and not located along frequented roads. A number of fallen or dead trees should be left in such afforestations as nesting for beneficial animals, especially birds, but also for a huge number of parasitic, predacious, and polinating arthropods and insect pathogenic microorganisms, thus increasing resistance of cultures against harmful herbivores.

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2. Adjustment of the species composition to local site conditions The use of native species and local ecotypes of trees and shrubs best adapted to the regional climate and soil should be a general principle in shelterbelt planting. The recommended components for Polish and central European areas have been listed in many scientific papers, books, and manuals, but because of economic reasons and insufficient coordination, nursery production does not meet the actual demand for seedlings (too narrow a scope of native wild species and simultaneously an overabundance of ornamental cultivars). However, situations or requirements such as the following may call for the use of nonnative or even exotic species: • Atmospheric and soil pollution forcing the use of more resistant species (black pine, plane tree, horse chestnut, red oak) • Good increment and favorable wood characteristics (Euro-American poplar cultivars, Douglas fir, red oak) • Fruit and melliferous species that, apart from direct use by man, are also attractive for beneficial arthropods and birds, stimulating biodiversity (many species of trees and shrubs) • Some ornamental forms traditionally planted

Purposeful dissemination of highly expansive species that threaten to dominate native associations in Poland, as for example, the black cherry or ash-leaved maple, should not be allowed, nor should native or exotic species indirectly posing hazards of spreading plant diseases or significant pests (e.g., berberry, bird’s cherry, alder buckthorn, white pine). 3. Continuity of shelterbelt existence in landscape structure To properly fulfill their protective functions, afforestations have to be persistent elements in the landscape. Hence it is necessary to secure their existence legally. It is also essential to recognize local residents’ attitudes toward shelterbelt plans and to establish valid legal records precluding groundless afforestation removal. Composition and management of afforestation species are also of great importance for ensuring their long-lasting benefits. Biogroups should be differentiated according to fast-growing and long-lived species in proportions adequate to site conditions. Tree generation exchange should be carried out over several dozen-year periods. On the basis of the RCAFE research, the systems of afforestation barriers proposed for wet habitats in Poland (alder and riparian plain forest sites) should contain 60 to 70% species of 30- to 70-yr felling cycles (black and white poplars and their selected hydrids, black alder, birch and willows), and 30 to 40% long-lived species (mostly European ash, oaks, larch, elms), ensuring persistence of shelterbelt structure for long time spans (150 to 250 or more years). In drier areas of moraine plateau, the components typical for horn beam-oak associations should dominate (oaks, linden, beech, horn beam, elms, birch, rowan, sycamore) with small admixtures of larch, Scotch pine, Norwegian spruce, wild forms of pear, apple and plum, and numerous shrub species. In the least fertile sandy or weakly agrillaceous soils, greater use of Scotch pine, European larch and sessile oak, rather than sycamore, ash, elms, horn beam and pedunculate oak, is recommended, with a steady component exchange,

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beginning from 60 to about 100 years. In all these cases, the component exchange should be carried out by single-tree selection cutting or small group felling. Neither one-row and allee-type afforestations nor many-row belts and small-area woodlots can be cut by means of clear cutting. Principles of management and utilization of afforestation should be mandated in space management plans of communes. 4. Economical management of farmland Spatial arrangement of shelterbelts should be to the maximum degree connected with linear elements of the fields’ infrastructure, locating them in one- to four-row strips along roads, watercourses and on the borders of different land use forms (grassland-field ecotones, riparian lines of water bodies, etc.). In those cases when they must be run across arable fields, it is advisable to use low-utility areas. In areas of intensive farming, shelterbelt participation should not exceed 2.5 to 4% of arable fields. Areas with poor soils should also be cautiously qualified for persistent reafforestation because reserves of agriculturally nonutilized fields may facilitate combining farming with other forms of economical activities, such as agrotourism, small forms of services, and crafts. This aspect is particularly important for regions with long agricultural traditions and high unemployment levels. In such cases, planting of shelterbelts would be a noncontroversial and environmentally advantageous form of management of selected set-aside fields. It should also meet the tendency to manage nature conservation and landscape protection resorts in the areas withdrawn from the agricultural use, which are more and more popular in the European Community countries (Bastian 1994, Latesteijn 1994, Bacharel and PintoCorreia 1999). 5. Nature protection support and biological control enhancement The functions involving biodiversity preservation in rural areas are best performed by woodlots of rich species composition, growing on differentiated sites, and linked by shelterbelts with greater areas of natural or seminatural ecosystems (forest, swamps, and rushes). Rationally managed networks of biogeochemical barriers usually contain well-functioning refuges of many species and ecological corridors for their migration, as confirmed by extensive studies on biological resources in the Agro-ecological Landscape Park near Turew (Karg and Ryszkowski 1996, Karg 1997, Ryszkowski et al. 1998, 1999). Their differentiation by biocenotical admixtures of fruit or melliferous plants, as well as by limited removal of dead trees, favors creation of nesting habitats for birds and increased attractiveness for invertebrates beneficial for agriculture (spiders; pollinating, parasitoid and predacious insects and mites; different saprophagous forms) and entomopathogenic microorganisms (Ba l azy 1994, 1997, Hemmati et al. 1997, Ba l azy et al. 1998). Crop protection development prospects (Lipa 1998, 1999), considered among nonchemical methods, widened utilization of a habitat’s natural potential to prevent pest outbreaks. Although the role of shelterbelts and woodlots in preservation of beneficial organisms — mostly entomophagous arthropods — has usually been strongly stressed, the practical plant-protection measures have often been neglected. Ferron (2000) shows the necessity for managing rural landscapes habitats suitable

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for natural populations of beneficial organisms with the primary aim to include them in integrated pest control methods, observing general principles of biodiversity preservation. 6. Increase of the economic value of shelterbelts Although afforestations are mainly introduced in farmland for their protective functions, they make it possible to obtain various products, timber included, with no harm to their principal role. To fully utilize this potential, certain conditions must be fulfilled, of which the most important are: • Planting tree species yielding high quality timber • Proper stand management to obtain possibly large amounts of high quality timber • Establishment of methods and quotas of timber yields to secure the continuity of shelterbelt functioning • Indication of ways for tree-cover renewal which ought to be carried out immediately after timber removal

CONCLUSIONS The problem of mid-field afforestation has not yet been ultimately settled by Polish law. No proper system of economic incentives has thus far been introduced to encourage farmers to establish shelterbelts. The adoption of such a system would comply with European Union Directive 2078/92 defining subsidies to compensate losses resulting from extension of economic activity involving proecological technologies and supporting nature protection. In the postwar period, several planting actions were undertaken, but only some were successful (Zaja˛ czkowski 1996, Budzyn´ ski 1997). Fifty years of Polish practice has taught us it is extremely difficult to maintain a shelterbelt in a proper state unless it is supervised by a landowner or administrator, or if location generates conflicts with neighbors. For these reasons, a person or institution should be designated responsible for the maintenance of every afforestation. Farmland afforestations are indispensable factors supplementing the “country’s program of afforestation increase” since they fulfill the majority functions. Hence, it is necessary to coordinate closely mid-field afforestation and the country’s reafforestation projects, both on the general scale and in particular watersheds. The number of shelterbelts, the spatial structure of their networks, and their species composition should be adjusted to the kinds and intensity of environmental threats that they must counteract. They should be designed according to the principle of maximum high quality farmland economy. Shelterbelt establishment and protection should be considered a priority in regions of serious water shortage and pollution (especially nonpoint pollution) and in areas threatened by various kinds of erosion. In areas of diversified relief, their water protective functions ought to be combined with anti-erosive ones.

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Lamin L. A. 1983. Persistence of shelterbelts in the Northern Kulunda. In Vozobnovlenie i ustojchivost lesov Zapadnoj Sibirii. Ed. V. N. Gabeev. Izdatelstwo Nauka. Moskva: 150–169. 173 pp. [in Russian]. Latesteijn H. 1994. Ground for choices: a policy oriented survey of land use changes in the European Community. In Functional Appraisal of Agricultural Landscape in Europe. Eds. L. Ryszkowski, S. Ba l azy. Research Centre for Agricultural and Forest Environment, Pol. Acad. Sci. Poznan´ : 289–297. Lipa J. J. 1998. Applied entomology and plant protection in 21st century. Wiadomo´sci Entomologiczne 17 (Supplement): 51–77 [in Polish]. Lipa J. J. 1999. Does species diversity restrict outbreaks of agrophagous pests? In Uwarunkowania · ochrony róznorodno s´ci biologicznej i krajobrazowej. Eds. L. Ryszkowski, S. Ba l azy. Zak l ad Badan´ S´ rodowiska Rolniczego i Les´ nego PAN. Poznan´ : 81–98 [in Polish]. Mannion A. M. 1995. Agriculture and Environmental Change. Wiley. Chichester. 405 pp. Medvedev V. V., Soko l ovaki A. N. 1992. Concept on efficient use of soil cover in the Ukrainian. In Comparisons of Landscape Pattern Dynamics in European Rural Areas. EUROMAB Research Program “Land Use Changes in Europe and their Impact on the Environment.” Seminars Rennes-Lieury-Kiev: 63–69. Meynier A. 1976. Typologie et chronologie du bocage. In Les bocages: histoire, écologie, économie. CNRS-ENSA et Université de Rennes. Ed. M. J. Missionier. Rennes: 65–67. Pan-European Biological and Landscape Diversity Strategy. 1996. Council of Europe. UNEP. European Centre for Nature Conservation. Amsterdam. 50 pp. Pape L. 1976. Bocage et voies romaines dans le département des côtes-du-Nord. Essai de chronologie. In Les bocages: histoire, économie, écologie. CNRS- ENSA et Université de Rennes. Ed. M. J. Missionier. Rennes: 75–78. Petrov P., Skachkov B. 1987. Forests and fields. Science in the USSR 4: 88–99. Prusinkiewicz Z., Pokojska U., Józefkowicz-Kotlarz J., Kwiatkowska A. 1996. Studies on functioning of biogeochemical barriers. In Dynamics of an Agricultural Landscape. Eds. L. Ryszkowski, N. R. French, A. Ke˛ dziora. PWRiL. Poznan´ : 110–119. Rauce K., Kyrstja S. 1986. The soil threats control. Agropromizdat. Moskva. 222 pp. [in Russian]. Read R. A. 1958. The Great Plains shelterbelt in 1954. Great Plains Agric. Council Publ. No. 16, 125 pp. [in Russian]. Read R. A. 1964. Tree Windbreaks for the Central Great Plains. USDA. Forestry Service, Agric. Handbook No. 250. 68 pp. Ryszkowski L. 1975. Review of studies of the effects of afforestations on adjacent field habitats carried out in Turew. Zeszyty Problemowe Poste˛ pów Nauk Rolniczych 156: 71–82. Ryszkowski L. 1987. Ecological agriculture. Zeszyty Problemowe Poste˛ pów Nauk Rolniczych 324: 15–42 [in Polish]. Ryszkowski L., Ba l azy S. 1991. Strategy of living resources protection in Poland. Zak l ad Badan´ S´ rodowiska Rolniczego i Le´snego PAN. Poznan´ . 95 pp. [in Polish]. Ryszkowski L., Ba l azy S., Jankowiak J. 2000. Program of mid-field afforestation increase. Poste˛ py Nauk Rolniczych 5/287: 83–106 [in Polish]. Ryszkowski L., Bartoszewicz A. 1987. Impact of agricultural landscape structure on cycling of inorganic nutrients. In Ecology of Arable Land. Eds. M. Clarholm, L. Bergstrom. Kluwer Academic Publishers. Dordrecht: 241–246. Ryszkowski L., Bartoszewicz A., Ke˛ dziora A. 1997. The potential role of mid-field forests as buffer zones. In Buffer Zones: Their Processes and Potential in Water Protection. Eds. N. Haycock, T. Burt, K. Goulding, G. Pinay. Quest Environmental. Harpenden: 7–20.

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Zaja˛ czkowski K. 1996. State of afforestation in Poland and actual problems of their development. Forestry Research Institute. Scientific documentation. 15 pp. [in Polish, unpublished]. Zaja˛ czkowski K. 1997a. Afforestations in spatial planning. In Znaczenie zadrzewien´ w krajobrazie rolniczym oraz aktualne problemy ich rozwoju w przyrodniczo-gospodarczych warunkach Polski. P l ock: 111–121 [in Polish].

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CHAPTER

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Land Units and the Biodiversity of Forest Islets: From Satellite Images to Ground Analysis Marc Galochet, Vincent Godard, and Micheline Hotyat

CONTENTS Introduction............................................................................................................318 Land Units and the Biodiversity of Forest Islets..................................................318 Defining Land Units.....................................................................................318 Forest Islets: From Land Units to Vegetal Diversity...................................319 Wooded Areas Shaped by Man ...................................................................319 Remote Sensing to Delimit Land Units and Establish the Location of Forest Islets ......................................................................................322 Remote Sensing to Determine the Forest Islets ..........................................322 The Choice of Samples in the Land Units: From Medium to Large Scale............................................................................................................323 How Can the Biodiversity of the Forest Islets Be Established on the Ground? ................................................................................................................324 The Choice of Sampling Unit: The Transect ..............................................324 Orientation of the Transects.........................................................................325 Transect Number ..........................................................................................326 Distribution of the Transects........................................................................328 Conclusion .............................................................................................................329 References..............................................................................................................329

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INTRODUCTION The landscape of extensively farmed countryside in Poland, as in France, is made up of a mosaic of agricultural plots linked to noncontiguous wooded areas of various sizes and shapes, sometimes connected to one another by hedges or wooded corridors. These wooded areas have been and still are greatly influenced by man and his methods of cultivation. The biodiversity of forest islets thus depends as much on human actions as on the environmental conditions. What is the influence of forest management methods and forestry traditions on the biodiversity of forest islets? What kind of diversity, in terms of structure and function, characterizes forest islets that have found a niche in ecosystems dominated by intensive farming? To illustrate our remarks, we use a sector in Greater Poland, representative of extensively farmed countryside, and situated approximately 50 km to the south of Pozna n´ . First, the land units are delimited with the help of satellite data. Second, an automatic extraction process pinpoints the forest islets. Finally, the biodiversity of these forest islets is analyzed using a frame sample.

LAND UNITS AND THE BIODIVERSITY OF FOREST ISLETS Research on land cover units allows us to look at the forest islets in context and to understand the environmental conditions in which they are best situated. The biodiversity of the forest islets can be appreciated when their spatial distribution and the modifications that have taken place over time are considered at one and the same time. This leads to cross-referencing the environmental conditions as well as the uses of the land have had and still have an influence on the biodiversity of the islets. Defining Land Units The term land unit is difficult to pin down in that there is still a certain amount of uncertainty in its definition, indeed in its conception. Nevertheless, some aspects of the term can be fixed: • Overall, a land unit is homogenous and constitutes a whole with its own identity, • A land unit can be defined by the fact that there is sufficient difference between it and the units which surround it. This difference allows the spatial boundaries of the unit to be defined, and its characteristics to be discerned. • This said, homogenous does not mean monotonous and does not imply that there is only one feature appearing repeatedly. On the contrary, a land unit is made up of diverse features, organized in such a way that they give the unit its originality and its identity. As a consequence, to delimit a land unit, it is necessary to list all the features that make it up, to analyze their layout, and to bring their integration in space to the fore.

Thus, in the words of Marcel Papy, “units of relatively equal appearance” are made up of large masses of land cover (communication networks, residences, agricultural

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areas, woods, forests, and so on), as well as features, such as the size and shape of the plots (whether these are agricultural or forest plots), the types of land cover, and the topography (Papy, 1992). Each land unit is thus defined by a particular physiogomy and therefore a structure that expresses the uses to which it is put, that is to say, the use of the soil. Forest Islets: From Land Units to Vegetal Diversity Forest islets, when seen as land units, can be approached on two complementary levels (Hotyat et al., 1999): • On a regional scale in order to determine the organization of land units in its totality, by distinguishing a mosaic of agricultural plots, which constitute the agrosystem, and the woods, which represent the sylvosystem (Figure 14.1). By thus looking at the wooded areas in their regional context among the other landscape elements, we can reveal their relationship toward each other in space. This scale allows us to appreciate the fragmentation of forest cover (Harris, 1984). • On the woodland scale, we can appreciate structural and vegetal diversity in their totality, both of which express the internal functioning and structure of the forest islets.

The fragmentation of forest cover and its spatial organization have an effect on the plant biodiversity of the forest islets. In fact, these wooded areas of different sizes can be considered “islands” totally isolated in both coastal and continental areas. However, these continental islands or forest islets, like the summits of isolated mountain chains, that come within the boundaries of agrosystems have specific characteristics, which evoke the insular biogeographical theory (MacArthur and Wilson, 1967). The theory of dynamic equilibrium elaborated by MacArthur and Wilson in 1963 and 1967 respectively, explains the constitution and evolution of insular ecosystems through the conjunction of two opposing phenomena: the immigration of new species and the extinction of species (Ramade, 1994). Forest islets find themselves all the more easily enriched by migrating species since the places from which they come are nearby. Inversely, the extinction rate is all the higher since the forest islets are isolated. The insular theory which looks at the distance that separates islets from one another and from other source habitats, as well as their size, does not, on the other hand, take into account the respective density of species, their abundance-dominance, their capacity to produce seeds, and the possibility they have to colonize the environment, or the potential of said environment. This theory greatly informed the concepts of the evolution of biocenosis in the 1960s; nevertheless, it is appropriate to add to this theory environmental data and to take into consideration the influence of human action effected on the environment. Wooded Areas Shaped by Man Most wooded areas are indeed shaped by forest management activity. The aftermath of work on trees and forestry traditions have a lasting influence on the structure

Shaded composition of General Ch l apowski’s Agro-ecological Park (Greater Poland), Satellite Image SPOT HRV-17, June 1997.

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Figure 14.1

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and the plant diversity of the forest islets (Galochet, 2001). All these forested plots are largely influenced by human activity and local history, notably forestry traditions. The wooded areas in Greater Poland are marked, as if in indelible ink, both by a form of forestry inherited from the Prussian invasion and then by almost half a century of collectivism. These are important events which marked the established societies of the period by modifying their economic, social, and agricultural structures over several generations. Yet, as the historian Fernand Braudel wrote in his Grammar of Civilisations, “the past of a civilisation is […] only the history of continual borrowings which they have made from one another, over the course of centuries, without, however, losing their specificity, or their originalities.” Thus, after the third partition of Poland in 1795, which caused it to disappear from the political map of Europe, Greater Poland was under Prussian rule until 1918, the date when Poland became independent once more following the defeat of the central empires, and the Russian Revolution (Le Breton, 1994). This occupation had serious consequences for forestry traditions and the forest environment, something that can still be seen today through the numerous mono-specific and even aged linear formations most frequently composed of Scotch pines (Pinus sylvestris). Nevertheless, an exception is found in Greater Poland, a nobleman’s estate — General Dezydery Ch lapowski (1788–1879), a prominent landowner, whose landscape improvements survive to this day. Recruited into the Napoleonic army at the age of 18, after having studied at the Military School in Paris, he became the Emperor’s aide-de-camp and accomplished some great military campaigns at his side, something that allowed him to travel across western Europe. On his return to Poland around 1820, he devoted himself to his land (about 10,000 ha)* and made some important developments in forestry and agriculture, influenced by various observations he had made over the course of his numerous trips to England, Scotland, Ireland, and France. He planted lines of trees along the edges of pathways, made countless experiments with drainage, crop rotation, and seed testing, built hedges to act as windbreaks and to limit erosion from wind, introduced exotic touches such as the locust tree, and established forest islets. The ideas of General Ch l apowski were adopted by some of his noble friends who thus spread his agroforestry model. But this model did not extend to territories outside Greater Poland because of the proximity of the frontier between Prussia and Russia. These old forestry developments, which modified and shaped wooded areas, still influence countryside diversity today, something that can be identified using satellite images. A methodology capable of defining land units, identifying them on the ground, analyzing them, and ensuring their cartographic representation must still be finalized. Remote sensing, where it is adapted to an overall view of the principal types of land cover seen from above, on a regional scale, provides these possibilities.

* The General Ch l apowski Landscape Park (or Agro-ecological Park), was created in 1992 and is managed by the Research Centre for Agricultural and Forest Environment of the Polish Academy of Sciences.

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REMOTE SENSING TO DELIMIT LAND UNITS AND ESTABLISH THE LOCATION OF FOREST ISLETS The distribution, size, and shape of forest islets on extensively farmed plots, in Poland as in France, are determined by the environmental conditions and the intensity of their cultivation by man. The confrontation of natural and cultural factors (Hotyat et al., 1997) explains the specific vegetal, locational and countryside diversity that can be perceived through the analysis of remote sensing images. Remote Sensing to Determine the Forest Islets To what extent can forest islets in extensively farmed areas, considered geographical and radiometric land elements, be individualized in relation to other types of land cover? Remote sensing uses the physical properties of the objects under observation to obtain information about their nature, through electromagnetic radiation that these objects reflect. In this way, objects can be differentiated from one another by their own individual spectra. Using a specific color composition (Figure 14.1; vegetation index, Roberts filter on this index, and analysis of the principal components, coded respectively in blue, green and red) we can appreciate the spatial distribution of wooded areas (in shades of green) in comparison to other types of land cover (cultivated fields in orange, and bare ground in blue), and we can detect their structure and their dominant features. Remote sensing creates a dual interest. On the one hand, it gives us numerical information by means of the different channels and their spectral resolution, and, on the other, it provides an exhaustive study, a sort of objectivity, about the areas studied as a whole. However, it must not be forgotten that objects of a smaller scale than that of the spatial resolution cannot be spotted (unless very strong radiometric contrasts are used) and that topographical variations, due to the effects of shade, can bring about confusion in the identification of the objects that make up the landscape. We must therefore be careful when it comes to interpreting data; in Laurence Le Du’s words, “The use of close-range infrared, and of medium-wave infrared, in the study of landscapes is necessary, but obliges us, to an even greater extent than for visual observations, to make a good interpretation of the data which necessitates a good knowledge of the ground. We must not only link the information from the images to a specific reality, but also decide to what extent this reality can be considered to be a proper criterion for defining a land unit” (Le Du, 1995). This situation raises questions of automatization: to what extent are these steps possible when you take into account that certain features that are too small (hedges, plot boundaries, isolated trees and so on) are not detectable, while others, that are not visible in the landscape, are revealed by means of reflection (soil moisture levels, the variation of chlorophyllous activity, and so on). To limit these disadvantages, it is necessary to include other information, such as that provided by topographical maps, aerial photographs, cadastral surveys or any other cartographic documents or statistical data. This cross-referencing of data allows

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Figure 14.2

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Extraction of forest islets by the masking method and distribution of the transects.

us to combine the rapidity of satellite data treatment, the precision of other sources of information, and the possibility of finally reaching some form of generalization. Moreover, this step means a trans-scalar approach to space is favorable. To perceive the forest islets in their totality, a procedure of extraction by masking is carried out (Figure 14.2). This population of islets forms the base of the survey, from which individual islets are selected for study. The Choice of Samples in the Land Units: From Medium to Large Scale This multisource and multiscale approach to space integrates a maximum amount of information, mostly complementary. However, the documents have different scales, which obliges us to scale the different documents, then geo-reference them. However, the depth of this kind of approach which fits different scales together, favors the division of the land into units through the use of satellite images, from the midst of which representative samples are selected as necessary to the analysis of the next scalar level down. In this study, satellite data, aerial photographs and ground surveys, supplemented with the various maps available, will be used in succession. Remote sensing thus offers us the possibility of systematic division of space with the help of software for the treatment of images; information about the area under study can be given over a period of about 26 days because of the repeated

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passage of the SPOT satellite over the same zone. The nature and structure of objects larger than a pixel are detectable. Information that is not directly detectable in the landscape values, such as the hydric stress of plants and the intensity of chlorophyllous activity, is revealed by radiometry. Aerial photography informs us about landscape structures and the texture of objects; the smallest landscape features are detectable, and stereoscopic vision allows us to see the contours of the area under study. Then, the ground survey gives meaning to all these components. Finally, the complementary documents allow us to check the meaning of certain objects, to extract certain pieces of information, and to find out about specific types of land cover. If the methodological schema seems simple, note that putting it into practice is much more complicated.

HOW CAN THE BIODIVERSITY OF THE FOREST ISLETS BE ESTABLISHED ON THE GROUND? The biodiversity of a forest islet is a result of its external environment (the form and the nature of its boundaries) and internal context (the intensity of forest cultivation, the distribution of the plots and so on). The area, the perimeter, and thus also the density of each forest islet are determining factors when it comes to the appreciation of their characteristics. Only implementing a ground survey system can allow us to characterize the biodiversity of these islets. This step comprises several stages: first, a census of the population must made and is done with the help of isolation of the forest islets from their context in order to make their spatial distribution, shape, and size stand out. Then certain islets are selected before the ground survey procedure is launched. Finally, this step as a whole requires some adjustments, e.g., the choice of transect as a sampling unit, the direction, the spacing, the selection of the individual islets surveyed. The Choice of Sampling Unit: The Transect With regard to areal frame sampling, if one wishes to describe the totality of land-cover types, it is necessary to use the technique of nonaligned systematic sampling of the areas under survey in order to make up the sample (Godard, 1991; Eastman, 1995). This technique ensures a uniform distribution of the sample over the whole of the territory, while avoiding any bias caused by the regularities to be found in the landscape. On the other hand, when we are concerned with just one type of land cover, characterized by objects that are generally small, compact, and “badly” distributed, and when, moreover, it is necessary to list their external and internal zones of contact, then it is practically out of the question for this type of sampling which looks at points (or links) to select a utilizable sample. Because of this, we used transect sampling. The transect method is usually based on a series of straight parallels at regular intervals which cross the whole of the zone under study. The ground survey consists

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in measuring the distance of each change in physiognomy, or even of facies, encountered in crossing a forest islet, from the starting point of a transect. The nature of the point of contact at the entrance to the wood is localized and then researched, as is also the case for the point of exit. Then, each transition inside the wood is measured in relation to the entrance point. The homogenous zones on the one hand, and on the other the zones of transition, are researched with regard to their structure, strata, dominant components, abundance-dominance of the main species, management method, and so on. In addition to the qualification and quantification of the transitions, the transect method allows us to evaluate the different facies, their distribution and number, all in the absence of previous knowledge of the ground. It also allows us to carry out a few ratio calculations, and therefore also calculation of surface area for the different facies encountered. It is also acknowledged that the transect method ensures minimal but sufficient control for the nonsupervised remote sensing treatments (Fournier and Gilg, 1985). On the other hand, still in the framework of remote sensing treatments, the transect method provides few informative pixels; the ground survey can, in fact, provide only information about a narrow strip of land. Because of this fact, it is difficult to allocate facies to pixels, although this allocation is necessary for the initialization of supervised treatments. Finally, with the transect method, it is particularly important to take into account problems of progression and the avoidance of obstacles in facies-pixel allocation. Recording the trajectory with the aid of a GPS (Global Positioning System) type satellite-positioning instrument is particularly recommended. Although it is not easy to match the ground and satellite images with the transect method, the possibility of perceiving the transitions (lengths and shapes) and of indicating between which facies they occur means that we have retained this method of exploring the land. In order to put it into practice, it was necessary to determine the azimuth of the transects, their spacing and their number. Orientation of the Transects The risk of any systematic method is to fall foul of the regularity of the landscape which may not have been detected when sampling was carried out, leading to the over-representation of certain types of land cover in relation to others. To avoid this pitfall, we chose to test the main directions followed by the landscape. These directions are followed according to the way the forest is divided into plots, and to the felling areas, the tracks and so on. This information is included in the satellite images of the zone under study. In order to extract it, we used Fourier’s transformation analysis, which transposes the image into the area of spatial frequencies where “the representation of periodicity takes a linear form, orthogonal to the direction of the periodicity to be seen in the image” (Robin, 1995 p. 215). We found from this investigation that the most common direction had an azimuth of 30° in relation to north (Figure 14.3). Therefore, we oriented the transects perpendicular to this direction, that is to say at 120° east, in order to probe the underlying forest phenomena to the greatest possible extent.

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Fourier transformation applied to the forest islets of General Ch l apowski’s Agroecological Park (Greater Poland).

After having determined the direction of the transects, their spacing and their number remain to be defined before moving on to the ground phase. Transect Number We have previously stressed the relation that exists between biodiversity and the density of the forest islet. The latter is not easy to see, either on the ground or through images. It is therefore necessary to use other parameters, correlated to density, that are more easily perceived. Among these, the size of the forest islets is probably the simplest. It remains to be seen if, for General Ch l apowski’s Agroecological Park (our study zone), the size and the density of the forest islets are sufficiently correlated for it to be possible to substitute one for the other. If the correlation is judged to be sufficient, it will then be possible to stratify the population of the forest islets in three classes (small, medium, and large islets), then to sample them according to their size and thus obtain a good distribution of the survey points in relation to the supposed biodiversity. The experiment was carried out on sections compatible with the sections used by the IFN (Inventaire Forestier National, or French Forestry Inventory), e.g., copses,

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with a total surface area between 5 and 50 ares; groves, with a total surface area between 50 ares and 4 ha; and forests, with a surface area of above 4 ha (IFN, 1985). Moreover, the spatial resolution used, of 10 m width per pixel, does not gives us any information about sparse trees or any surface areas less than 5 ares. In fact, the extraction of forest islets had to be carried out using the same satellite data as that used to calculate Fourier’s transformation (see above). Because of the restrictions of time, these extractions were carried out on digitized topographical maps with a 1/50,000 scale. This situation calls for two comments: • First, that there is a time difference — the last update of the maps (in 1992) precedes the satellite data (from 1997), which is practically contemporary with the ground data. Some differences are thus to be expected between the ground survey and the digitized data. • Second, due to problems related to cartographic representation, the existence, the size and the localization of the forest islets are subordinated to the presence of other cartographic objects that are superimposed upon them, perhaps explaining why the extraction of the forest islets left only objects of 9 pixels width, in other words, 9 ares.

In that we worked with the Idrisi software, the density factor (Ic), taken from Claude Collet’s book (Collet, 1992, p. 133), had to be adapted to the features of a squared grid. In our example, the following formula is used: Ic =

Az 2 P  z  4

with Az, standing for the area of the islet, Pz for the perimeter of a square object of the same area of the islet Az. Theoretically, it varies from the value 1, which represents a square object of maximal density, to the value 0, which is an object without surface area of an infinite length. In practice, certain wooden corridors can have a factor close to 0. Having made these comments, it is now possible to analyze the relationship existing between the size and the density of forest islets at the heart of General Ch l apowski’s Agro-ecological Park. If forests (in the IFN’s sense of the word) are excluded in order to keep only forest islets, a linear relation of a relatively strong intensity (R = 0.7) can be made clear between surface area and density, which is significant and carries a risk of error less than 1 in 1000. It therefore seems useful to try to stratify the islets according to whether they are small, medium, or large. In order to do this categorization, the density of the islets was recoded according to their size, using the IFN criteria described above. This recoding proved to be very pertinent, for the groups clearly differ from each other where the criterion of density is concerned (Figure 14.4). Moreover, an analysis of variance, carried out on the groups formed in this way, confirms that their difference is significant with a risk of error less than 1 in 1000.

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Density of the forest islets when divided into three size groups.

The stratification of the islets gives rise to the following distribution within the limits of General Ch lapowski’s Agro-ecological Park: 101 copses, 94 groves, and 34 forests. But the samples within each stratum must still be provided. Distribution of the Transects Where the spacing of the transects is concerned, satellite images can, once again, be useful. Fourier’s transformation indicates the direction of the highest spatial recurrences (Figure 14.3), but does not give us a direct view of the rate (the distance) of the regularity relating to this axis. Methods coming under the heading of variographic analysis were successfully put into practice on a number of occasions on various study zones in order to determine the rate of sampling preceding the ground analysis (Godard, 1994; Fournier et al., 1997). They were applied over the entirety of survey zone and on the totality of the types of land cover, which was not the case for our study ground in Poland. After overall analysis of the distance between islets, the transects are placed at regular intervals of 500 m, generating an aligned systematic sampling. In this way, 31 transects were marked (Figure 14.2) which allowed us to extract 93 transect segments (that is to say, a section of transect that crosses a forest islet). Their distribution is as follows: 22 segments for the copse stratum and 34 for the groves. Each segment crosses only one islet in its group. On the other hand, the case of the forests is a little different in that the extraction method and the intensity of the probing would have led to over-representation with regard to the surface area of the forests. That is why we have eliminated from this process the two large forest masses, 328 and 164 ha in size, respectively, which are hardly representative of the other islets in the forest group. Therefore, we increased the distance between the transects,

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moving from 500 m to 1000 m, exclusively for this stratum. In the end, 9 segments were examined out of the 34 islets of this stratum.

CONCLUSION Remote sensing allows us to define the land units at the heart of which the main plant types are identifiable, and the forest islets stand out individually. Supplementing information concerning soil moisture and chlorophyllous activity, satellite images reveal variations that relate to the vertical and horizontal structures of the plant cover. The reliability of this information nevertheless depends on the quality of the ground survey and above all on the inventory protocol put into place for the collection of samples. The method of making an inventory using transects allows us to perceive the contacts between forest formations and their agricultural environment, but also the contacts and the transitions between the facies that make up the forest islets. However, the allocation of the ground data, collected along a transect, to the pixels of satellite images is not simple, for they represent a narrow strip of information in the landscape. Yet it is necessary to make the most of it in order to establish a typology of the diversity of forest landscapes in the Ch l apowski Agro-ecological Park and constitutes one of the axes of research of this project that must use ground survey and satellite images jointly. The methodology developed here can be reproduced and will be applied in France in the Gatinais region with a view to making a comparative study. REFERENCES Collet C. (1992). Systèmes d’information géographique en mode image. Presses polytechniques et universitaires romandes, coll. Gerer 1’environnement, no. 7, Lausanne, 186 pp. Eastman J.R. (1995). Idrisi, un SIG en mode image (Version 4.0 et 4.1). CRIF. Lausanne. Fournier Ph., GIlg J.-P. (1985). Télédétection et observation terrain. Cours du GDTA. Toulouse. 22 pp. Fournier Ph., Geroyannis H., Godard V. (1997). Analyse variographique de données satellitaires pour déterminer la taille des unités d’échantillonnage. Exemple d’un inventaire d’occupation du sol en milieu agricole et forestier. In Annales Littéraires de I’Université de Franche-Comté. Cahiers de Géographie. 35: 85–89. Galochet M. (2001). Les îlots boisés, des lieux de diversité en terre de grande culture. Comparaison France et Pologne. Thèse de Doctorat en Géographie, Université de Paris IV — Sorbonne. 344 pp. Godard V. (1991). Utilisation conjointe de la télédétection et de I’enquete de terrain lors des inventaires d’occupation du sol. Recherche appliquée au Sahel sud-mauritanien. Thèse de Doctorat EHESS, IEMVT, Maisons-Alfort. 433 pp. Godard V. (1994). Apport de 1’analyse variographique pour déterminer la taille et 1’espacement des unités d’échantillonnage lors d’un inventaire d’occupation du sol en milieu naturel tropical, Bul. SFPT 136, 33–44. Harris L.D. (1984). The Fragmented Forest: Island Biogeography Theory and the Preservation of Biotic Diversity. The University of Chicago Press. Chicago. 211 pp.

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Hotyat M., Galochet M., and Liège F. (1997). Petits bois et leurs lisières dans les plaines de grande culture: « entre nature et culture ». Exemple pris dans le Gâtinais occidental, In La dynamique des paysages protohistoriques, antiques, médiévaux et modernes. Editions APDCA. Sophia Antipolis. 493–504. Hotyat M., Galochet M., and Liège F. (1999). Structure et dynamique des ilots boisés: intérêt de 1’étude multicapteurs et de 1’analyse diachronique. In Paysages agraires et environnement, S. Wicherek (Ed.), CNRS éditions. Paris. 357–370. IFN (1985). But et méthodes de I’inventaire forestier national. Ministère de 1’agriculture, Service des forêts. Paris. 67 pp. Le Breton J.-M. (1994). L’Europe centrale et orientate de 1917 à 1990. Nathan, coll. Fac. Histoire. Paris. 304 pp. Le Du L. (1995). Images du paysage. Télédétection, intervisibilité et perception: 1’exemple des Côtes d’Armor. Thèse de Doctorat, Universite de Rennes 2. 334 pp. MacArthur R.H., Wilson E.O. (1967). The Theory of Island Biogeography. Princeton University Press. Princeton, New Jersey. 203 pp. Papy M. (1992). Effets des structures agraires sur le ruissellement et 1’érosion hydrique. Bulletin de l’Association des Géographes Français 2, 115–125. Ramade F. (1994). Elements d’écologie. Ecologie fondamentale. 2nd edition. Edisciences International. Paris. 573 pp. Robin M. (1995). La télédétection: des satellites aux SIG. Nathan, coll. Fac. Géographie. Paris. 318 pp.

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Agrolandscape Ecology in the 21st Century Gary W. Barrett and Laura E. Skelton

CONTENTS Nature as a Model System ....................................................................................332 An Agrolandscape Perspective ..............................................................................333 Reducing Eutrophication at the Landscape Scale.................................................334 Academic and Disciplinary Fragmentation...........................................................334 Linking Urban-Industrial and Natural Life-Support Systems ..............................335 Conclusion .............................................................................................................337 Acknowledgments..................................................................................................337 References..............................................................................................................337

A new century causes us to reflect on the accomplishments and problems of the past century and especially to address challenges regarding the future. In this chapter, we outline five topics (perhaps some would term them problem areas) that ecologists, agronomists, and resource planners need to address if sustainable agriculture is to become a reality during the 21st century. As Albert Einstein once stated, “The significant problems we face cannot be solved at the same level of thinking we were at when we created them.” We feel that it is imperative that new approaches be implemented to address agricultural problems and to create opportunities at greater temporal/spatial scales. Barrett (in press) and Barrett and Odum (1998) term this new transdisciplinary approach integrative science. Goodland (1995) defined sustainability as “maintaining natural capital.” We suggest that the concept of sustainability can assist in the integration of ecology and agronomy. There have been several recent attempts to summarize the benefits supplied to human societies by natural ecosystems (e.g., Daily et al. 1997), as well as attempts

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to quantify the value of ecosystem services and natural capital on a large-scale basis (e.g., Costanza et al. 1997). These attempts lend evidence to our assertion that the time is right to consider and implement a new integrative approach to agriculture at the landscape scale. This chapter describes five guidelines to address this task.

NATURE AS A MODEL SYSTEM Natural ecosystems have endured far longer than conventional agroecosystems have been in existence. Intensive-input agriculture, as currently practiced in much of the developed and developing world, represents a waste of scarce, finite resources. Intensive-input ecosystems (i.e., systems focused on a single crop or product with maximum yield as a goal) do not sustain themselves but instead rely on large amounts of labor and subsidies (fossil fuels, fertilizers, and pesticides) for production. Typically a single crop occupies a field during a single growing season (a monoculture approach to agriculture). Problems arise when subsidies are applied at one level (species or single crop) and then used without further study at another level (community, ecosystem, or landscape). Problems intensify when that single crop is planted and cultivated to maximize yield. Furthermore, traditional practices of crop rotation and allowing fields to lie fallow are not common in modern agriculture. Processes that are thought to sustain natural systems, such as natural means of pest control and detritus accumulation (Altieri and Nicholls 2000), are often absent or discouraged in modern agricultural practices. Natural systems also contain a co-evolutionary system of checks and balances between herbivores and predators that aids in the regulation of potential pest species. Thus, insect and weed pests thrive in monoculture cropping systems where they are not out-competed by native species or consumed by predators. Lower abundance of pest populations in heterogeneous systems is most likely due to the presence of natural enemies (Karel 1991). Monocultures also attract specialist herbivores, thus providing low diversity of food sources for predators (Letourneau and Altieri 1983). Also, monocultures provide less refuge for beneficial insects, predators, and parasitoids than found in nature (Letourneau and Altieri 1983). A greater abundance of these desirable insects helps regulate populations of specialized herbivores. Conventional tillage results in loss of topsoil, loss of wildlife habitat, and increased rates of soil erosion, among other consequences. Alternatives to conventional tillage include no-tillage, reduced tillage, and low-input sustainable agriculture (LISA). Surface litter in reduced or no-till systems contributes to water retention and cooler temperatures in topsoil (Coleman and Crossley 1996). Surface litter also provides home to soil micro- and macroinvertebrates, bacteria, and fungi that aid in decomposition of stubble left after harvesting. Soil structure and invertebrate communities of no-till agricultural systems more closely resemble those found in natural ecosystems than those in conventional agricultural systems. Reduced or no-till agriculture encourages soil stratification which creates a variety of habitats for soil invertebrates (Hendrix et al. 1986). The presence of earthworms, for example, aids in organic matter decomposition (House and Parmelee 1985). Macrofauna, such as birds and small mammals, have also been

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found to be more abundant in no-till than in conventionally tilled cropping systems (Warburton and Klimstra 1984). Rates of decomposition are also slower in agricultural systems not subject to tillage (imitating decomposition processes in natural ecosystems); therefore, a constant supply of nutrients is available for mineralization. Arthropods and earthworms in no-till systems aid decomposition (House and Parmelee 1985). In addition to providing cover for invertebrates (House and All 1981), detritus helps to maintain cooler and moist soil conditions. Thus, there exists ample evidence that natural or polyculture systems not only require less subsidies but also have evolved regulatory mechanisms necessary to control insect pests, aid in nutrient cycling, and improve soil conditions. A challenge for the 21st century is to couple or integrate mechanisms found in natural systems with traditional cropping systems. Only an integrative approach will accomplish this goal.

AN AGROLANDSCAPE PERSPECTIVE Agronomic research and planning have traditionally focused on the field or agroecosystem level. More recently, however, several studies have addressed interchanges of insects between agricultural and surrounding landscapes (Ekbom et al. 2000). The science of landscape ecology considers not only the development and dynamics of spatial heterogeneity but also the exchanges of biotic and abiotic resources across heterogeneous landscapes, including how this spatial heterogeneity influences biotic and abiotic processes (Risser et al. 1984). Traditionally, a single field (agroecosystem) approach was employed to address questions and to solve problems related to problems or concepts such as pest management, restoring or conserving biotic diversity, reducing subsidy input, or improving crop yield (Barrett 2000). Thus, a new landscape or regional perspective is warranted. Just as societies learned that biotic diversity cannot be protected or conserved by a single-species approach (Salwasser 1991), we predict that resource managers and agronomists will learn during the 21st century that a single farm/field (agroecosystem) approach cannot, among other larger scale challenges, sustain agricultural productivity, reduce regional or watershed eutrophication, or regulate pest species. Rather, an agrolandscape approach is needed in which landscape elements (patches, corridors, and the landscape matrix) are patterned and managed to optimize factors such as insect pest control, biotic (genetic, species, and habitat) diversity, soil restoration, net primary productivity, nutrient retention, and landscape connectivity (Barrett 1992, 2000). This emerging field of study, based on the concepts of sustainability and linking ecological capital with economic capital (Barrett and Farina 2000), should provide solutions to such challenges as ecologically-based pest management (National Research Council 2000), ecosystem stress and crop yield relationships (Odum and Barrett 2000), role of corridors in helping to regulate arthropod populations (Kemp and Barrett 1989, Holmes and Barrett 1997), relationship of landscape structures to biological control in agroecosystems (Thies and Tscharntke 1999), and protecting biodiversity in agroecosystems (Collins and Qualset 1999). Fortunately, new agricultural practices at the landscape and regional scales (e.g., conservation tillage, no-till agriculture, strip cropping, crop rotation, and use of

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nitrogen-fixing cover crops) have in many cases reduced pest damage, created habitat for wildlife, and decreased the use of subsidies (pesticides, fossil fuels, and commercial fertilizers). This landscape perspective based on transdisciplinary approaches is likely to continue, deriving from nature that mutualistic, rather than competitive, mechanisms increase as systems become more complex. As societies mature (i.e., reach the human carrying capacity) during the 21st century (Barrett and Odum 2000), it is anticipated that these mutualistic interactions will accompany the maturation process. REDUCING EUTROPHICATION AT THE LANDSCAPE SCALE Agricultural practices have modified the nitrogen cycle found in nature. Although nitrogen is typically cycled in a rather closed manner in nature, nitrogen fertilizers applied to crops in massive amounts, to stimulate plant growth thus maximizing crop yield, are now being lost to agricultural systems in great amounts. Fertilizers are often applied in excess, causing nitrogen from commercial fertilizers to be released to the environment. A consequence of excess nitrogen at the landscape scale is contamination of watersheds and ground water. Nitrogen not consumed by plants in the form of nitrates seeps into ground water or is released into the atmosphere. This typically limiting resource (when combined with phosphorous in fresh water habitats) causes eutrophication (the growth of toxic algal blooms in lakes). Eutrophication is known to limit the survival of aquatic life and decrease biodiversity (Vitousek et al. 1997). Algal blooms create lakes that are uninhabitable to most forms of life. Excess nitrogen not only acidifies ground water, lakes, and streams but also acidifies soil, which drastically changes the microclimate for soil fauna, thus making plant survival difficult. Another concern is the possibility of decreased biotic diversity of plant species. Opportunistic species that respond well to increased nutrient input typically become dominant and suppress native species that do not grow well when exposed to excess nitrogen (Vitousek et al. 1997). Unfortunately, mature ecosystems (e.g., forests, prairies, and wetlands) are sometimes converted to agricultural fields, thus altering ecosystem processes and functions. An important function of wetlands, for example, is their ability to denitrify nitrates. Water is released from wetlands very slowly so that less fixed nitrogen is passed to rivers and estuaries. Therefore, societies must preserve wetlands. Forested lands and riparian zones also must be maintained to divert excess nitrogen from cropland (Vitousek et al. 1997). Thus, the patterns and heterogeneity of ecosystems within a landscape are key to regulating the nitrogen cycle. ACADEMIC AND DISCIPLINARY FRAGMENTATION The past two decades have witnessed a plethora of books and publications focused on habitat and landscape fragmentation (e.g., Harris 1984). Little attention,

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however, has been paid to academic fragmentation (see Barrett in press). Numerous new interfaced fields of study emerged during the latter half of the twentieth century, such as restoration ecology, ecological engineering, landscape ecology, ecological toxicology, and conservation biology. These fields of investigation, including agrolandscape ecology, have contributed to a clearer understanding of our natural world, including a deeper understanding of the relationships and emerging properties among various disciplines in the physical, biological, and social sciences. Unfortunately, however, institutions of higher learning have failed to promote and establish mechanisms or structures to administer these interdisciplinary fields of study. Within this context Barrett (in press) has suggested a transdisciplinary scientific field of synthesis termed integrative science, based on the noosystem concept to integrate, rather than continue to fragment, this academic process. Along those lines, we suggest a 2-1-2 (5-year) undergraduate degree — 2 years of liberal arts; 1 academic year internship; 2 years focused on either an applied or basic science major. The internship would permit undergraduates interested in areas such as agroecosystem or agrolandscape ecology to understand better the scale of and challenges associated with seeking solutions to these problems, as well as the opportunities afforded those with this holistic perspective. For example, Barrett et al. (1997) stressed the need to more fully understand processes (e.g., energetics, regulation, diversity, and evolution) that transcend all levels of organization. Unfortunately, most courses and disciplines focus more on reductionist science at the lower levels of organization (molecule, cell, and organism) rather than on holistic science at higher levels of organization (ecosystem, landscape, and world). An internship option should help elucidate the need to merge basic and applied science, to wed disciplinary and interdisciplinary approaches, and to appreciate how major processes transcend all levels of organization. This approach will help to ensure that fields such as agronomy and ecology become integrated during the 21st century. It will also demonstrate why net energy and net economic currency will lead to sustainable agriculture (and a sustainable landscape) rather than to maximize crop yield as a societal goal. Barrett (1989) notes that a sustainable society is characterized by the virtues of preventive medicine, critical thinking, and problem solving on a landscape scale. A citizenry educated in this manner will focus on concepts such as net energy and net economic currency rather than on goals such as maximum growth and agricultural productivity.

LINKING URBAN-INDUSTRIAL AND NATURAL LIFE-SUPPORT SYSTEMS One of the greatest challenges of the 21st century will be to link urban-industrial systems with natural life-support systems. Odum (1997) classified ecosystems based on the proportions of solar and fossil fuel energy used to drive the system. Most natural systems are driven entirely by solar energy. Agroecosystems are driven by both solar energy and subsidies, whereas urban systems depend mainly on enormous inputs of fossil fuel subsidies.

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Figure 15.1

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Model illustrating the need to link natural life-support ecosystems with urbanindustrial ecosystems, including a reward-feedback loop. (Modified after Odum 2001.)

Systems can also be classified based on the ratio of energy produced by primary production (P) to energy used for respiration or system maintenance (R). Natural and agricultural systems are termed autotrophic where P/R > 1. In contrast, urban systems are heterotrophic systems where P/R < 1. Barrett et al. (1999) defined sustainable systems as those systems or landscapes where long-term P/R ratios equal 1. Thus, to meet this definition it is imperative to link urban-industrial (heterotrophic) systems with natural (including agricultural) life-support (autotrophic) systems at the landscape scale (Barrett et al. 1999 describe this developmental process). Naveh (1982) and Odum (2001) refer to these fuel-powered urban-industrial systems as techno-ecosystems. A modern city, for example, is a major technoecosystem. Techno-ecosystems represent energetic hot spots on the landscape that require a large area of natural and agricultural countryside to support such systems. Wackernal and Rees (1996) note that techno-ecosystems have a very large “ecological footprint.” Figure 15.1, modified from Odum (2001), depicts the need to link urban-industrial and techno-ecosystems with natural life-support ecosystems. The analogy to a host-parasite relationship describes how these two entities, we hope, will co-evolve. It is important to note that if the parasite (city) takes too much from the host (lifesupport system), both will die. Cairns (1997) is optimiztic that natural and technoecosystems will co-evolve in a mutualistic manner. A landscape perspective, including the development of reward feedback mechanisms (Figure 15.1) between these two systems, should lead to the mutual linkage of urban and agricultural systems — systems that previously were linked when towns and villages served as the marketplace for farmers and the rural citizenry. Future generations will depend on this type of mutualistic behavior and transdisciplinary planning in order to manage ecologic and economic resources in a sustainable manner.

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CONCLUSION This chapter afforded us the opportunity to reflect on the agricultural enterprise during the past few decades, then to reflect upon agriculture during the 21st century. Crosson and Rosenberg (1989), in a special issue of Scientific America (September 1989, “Managing Planet Earth”) noted that “agricultural research will probably yield many new technologies for expanding food production while preserving land, water and genetic diversity. The real trick will be getting farmers to use them.” Essentially, Crosson and Rosenberg were correct. For example, farmers, ecologists, policy makers, and resource managers now debate the costs and benefits of transgenic crops (Marvier 2001), while societies remain concerned about land use practices, water quality, and biotic diversity. Interestingly, it is not only the farmers and practitioners who need to modify human behavior, but also society as a whole. Society appears to know and understand the benefit derived from quality landscape health, protection of scarce biotic and abiotic resources, and adaptation of a sustainable approach to food production. A primary goal during the 21st century must be to use this knowledge and understanding to develop not only a sustainable approach to agriculture, but to become a mature and sustainable society as a whole. The time appears right to take a major step in that direction. Children and grandchildren will likely not forgive unless we use this knowledge and understanding on their behalf in the very near future.

ACKNOWLEDGMENTS We thank Lech Ryszkowski for inviting us to contribute to this book. We especially thank Terry L. Barrett for her editorial comments and help with the preparation of this manuscript. The first author is indebted to the numerous graduate students and postdoctoral fellows at Miami University of Ohio who, over the years, encouraged him to reflect on sustainable agriculture at the ecosystem and landscape scales.

REFERENCES Altieri, M. A. and Nicholls, C. I. (2000) Applying agroecological concepts to development of ecologically based pest management strategies, Proceedings of a Workshop Board on Agriculture and Natural Resources Professional Societies and Ecologically Based Pest Management, National Academy Press, Washington, D.C., 14–19. Barrett, G. W. (1989) Viewpoint: a sustainable society. BioScience, 39, 754. Barrett, G. W. (1992) Landscape ecology: designing sustainable agricultural landscapes, in Integrating Sustainable Agriculture, Ecology, and Environmental Policy, Olson, R. K., Ed., Haworth Press, Binghamton, NY. Barrett, G. W. (2000) The impact of corridors on arthropod populations within simulated agrolandscapes, in Interchanges of Insects between Agricultural and Surrounding Landscapes, Ekbom, B., Irwin, M. E., and Robert, Y., Eds., Kluwer Academic Publishers, Dordrecht, the Netherlands, 71–84.

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Barrett, G. W. Closing the ecological cycle: the emergence of integrative science, Ecosys. Health, in press. Barrett, G. W., Barrett, T. L., and Peles, J. D. (1999) Managing agroecosystems as agrolandscapes: reconnecting agricultural and urban landscapes, in Biodiversity in Agroecosystems, Collins, W. W. and Qualset C. O., Eds., CRC Press, Boca Raton, FL, 197–213. Barrett, G. W. and Farina, A. (2000) Integrating ecology and economics, BioScience, 50, 311– 312. Barrett, G. W., Peles, J. D., and Odum, E. P. (1997) Transcending processes and the levelsof- organization concept, BioScience, 47, 531–535. Barrett, G. W. and Odum, E. P. (1998) From the President: Integrative Science. BioScience, 48, 980. Barrett, G. W. and Odum, E. P. (2000) The twenty-first century: the world at carrying capacity, BioScience, 50, 363–368. Cairns, J. (1997) Global coevolution and natural systems and human society, Revisa Sociedad Mexicana de Historia Natural, 47, 217. Coleman, D. C. and Crossley, D. A., Jr. (1996) Fundamentals of Soil Ecology, Academic Press, San Diego. Collins, W.W. and Qualset, C.O. (1999) Biodiversity in Agroecosystems, CRC Press, Boca Raton, FL. Costanza, R., et al. (1997) The value of the world’s ecosystem services and natural capital, Nature, 387, 253–260. Crosson, P. R. and Rosenberg, N. J. (1989) Strategies for agriculture, Sci. Am., New York. Daily, G. C., Alexander, S., Ehrlich, P. R., Goulder, L., Lubchenco, J., Matson, P. A., Mooney, H. A., Postel, S., Sch Tilman, D., and Wodwell, G.M. (1997) Ecosystem services: benefits supplied to human societies by natural ecosystems, Issues in Ecology, 2, Ecological Society of America, Washington, D.C. Ekbom, B., Irwin, M. E., and Robert Y., Eds., (2000) Interchanges of Insects between Agricultural and Surrounding Landscapes, Kluwer Academic Publishers, Dordrecht, the Netherlands. Goodland, R. (1995) The concept of environmental sustainability, Annu. Rev. Ecol. Systematics, 26, 1–24. Harris, L. D. (1984) The Fragmented Forest, University of Chicago Press, Chicago, IL. Hendrix, P. F., Parmelle, R. W., Crossley, D. A., Jr., Coleman, D. C., Odum, E. P., and Groffman, P. M. (1986) Detritus food webs in conventional and no-tillage agroecosystems, BioScience, 36, 374–380. Holmes, D. M. and Barrett, G. W. (1997) Japanese beetle (Popillia japonica) dispersal behavior in intercropped vs. monoculture soybean agroecosystems, Am. Midland Natur., 137, 312–319. House, G. J. and All, J. N. (1981) Carabid beetles in soybean agroecosystems, Environ. Entomol. 10, 194–196. House, G. J. and Parmelee, R. W. (1985) Comparison of soil arthropods and earthworms from conventional and no-tillage agroecosystems, Soil Tillage Res., 5, 351–360. Karel, A. K. (1991) Effects of plant populations and intercropping on the population patterns of bean flies on common beans, Environ. Entomol. 20, 354–357. Kemp, J. C. and Barrett, G. W. (1989) Spatial patterning: impact of uncultivated corridors on arthropod populations within soybean agroecosystems, Ecology, 70, 114–128.

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Letourneau, D. K. and Altieri, M. A. (1983) Abundance patterns of a predator, Orius tristicolor (Hemiptera: Anthocoridae), and its prey, Frankliniella occidentalis (Thysanoptera: Thripidae): habitat attraction in polycultures versus monocultures, Environ. Entomol. 12, 1464–1469. Marvier, M. (2001) Ecology of transgenic crops, Am. Scientist, 89, 160–167. National Research Council. (2000) Professional Societies and Ecologically Based Pest Management, National Academy Press, Washington, D.C. Naveh, Z. (1982) Landscape ecology as an emerging branch of human ecosystem science, Adv. Ecol. Res., 12, 189–237. Odum, E. P. (1997) Ecology: A Bridge between Science and Society, Sinauer Associates, Sunderland, MA. Odum, E. P. (2001) The techno-ecosystem, Bull. Ecol. Soc. Am., 82, 137–138. Odum, E. P. and Barrett, G. W. (2000) Pest management: an overview, in National Research Council Report, Professional Societies and Ecologically Based Pest Management, National Academy Press, Washington, D.C. Risser, P. G., Karr, J. R., and Forman, R. T. T. (1984) Landscape ecology: directions and approaches, Special Publication 2 in Illinois Natural History Survey, Champaign, IL. Salwasser, H. (1991) Roles and approaches of the USDA Forest Service, in Landscape Linkages and Biodiversity, Hudson, W. E., Ed., Island Press, Washington, D.C. Thies, C. and Tscharntke, T. (1999) Landscape structure and biological control in agroecosystems, Science, 285, 893–895. Vitousek, P. M., Aber, J. D., Howarth, R. W., Likens, G. E., Matson, P. A., Schindler, D. W., Schlesinger, W. H., and Tilman, D. G. (1997) Human alteration of the global nitrogen cycle: sources and consequences, Ecol. Appl., 7, 737–750. Wackernal, M. and Rees, W. (1996) Our Ecological Footprint: Reducing Human Impact on the Earth, New Society Publishers, Cabriola Island, British Columbia, Canada. Warburton, D. B. and Klimstra, W. D. (1984) Wildlife use of no-till and conventionally tilled corn fields, J. Soil Water Conserv., 39, 327–330.

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Agriculture and Landscape Ecology Lech Ryszkowski

CONTENTS Overview................................................................................................................341 The New Common Agricultural Policy (CAP).....................................................342 Sustainable Agriculture..........................................................................................344 Landscape Management in Development of Sustainable Agriculture..................345 Conclusion .............................................................................................................347 References..............................................................................................................348

OVERVIEW It can be argued that objectives for agriculture are inherently different from those for nature protection, and, therefore, it is unwise to rely on the agricultural management of land as the primary means for environmental protection. As agricultural productivity expanded, natural landscapes were converted to rural landscapes composed of cultivated fields, pastures, settlements and patches of nonarable habitats. Farmers, to a great extent, have been responsible for the development and stewardship of the landscape. Agricultural activity is focused on production; therefore, all available resources were used to maximize yields. This attitude led to neglecting the importance of all nonproductive elements of the rural landscape and, because of a lack of knowledge, resulted in the widespread treatment of small patches of wetlands, mid-field ponds, hedges, groves, and so on as idlelands, or habitats of no use. There seems to be little question that, because of this attitude, as cultivated fields were developed, to increase production, many nonproductive landscape elements were eradicated, leading to landscape uniformity. When the intensification of agricultural production increased to the point that the landscape’s capacities to buffer

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the side effects from farming were overcome — which was facilitated by loss of landscape diversity — environmental threats started to appear. Accelerated rates of water and wind erosion, diffuse pollution of water reservoirs, lowered ground water levels, increased frequency of floods, broader variation in microclimatic factors, outbreaks of crop pests, and many other phenomena brought by farming intensification began to be observed worldwide. Two reports on changes in the European environment (Stanners and Bourdeau 1995, European Environment Agency 1998), requested by the environment ministers for all of Europe, clearly documented environmental deterioration from agriculture, industry, urbanization and other human activities. The same situation in other parts of the world is evidenced by a variety of publications. Although there has been much more concern shown for environmental threats caused by industry or urbanization, agricultural activities have played an important role in overall human impact on the environment. Ground water quality can be decreased by high concentrations of nitrates brought by the use of artificial fertilizers and manure on cultivated fields. The spatial scale of these impacts can be enormous. Stanners and Bourdeau (1995), using the figures provided by model computations, reported that the nitrate concentrations levels in ground water from 87% of the agricultural land in Europe exceeded 25 mg·l–1 (the European Union target value) due to leaching from soils. The drinking water standard of 50 mg·NO3– ·l–1 was exceeded in 22% of the area. Light soils, high inputs of nitrogen fertilizers, and the loss of small nonarable habitats, such as permanent vegetation patches and mid-field wetlands and ponds, are the main factors leading to high nitrate passing loads into aquifers. Contamination of water by pesticides leached from soils, erosion, soil compaction, desertification, impoverishment of biological diversity, pest outbreaks, and other threats to agroecosystems have been recognized not only by scientists but more recently even by decision makers.

THE NEW COMMON AGRICULTURAL POLICY (CAP) These environmental considerations became an important issue during the formulation of the new Common Agricultural Policy (CAP) in the 1990s by the European Union (EU) within the context of Agenda 2000, issued in 1997, which included a revised EU policy on development. The CAP, which makes up one of the sectorial policies of Agenda 2000, proposes that farmers should observe a minimum standard level of environmental protection measures defined in the codes of good agricultural practices and that any additional environmental services should be financed by society through agro-environment programs. Enacting such administrative regulation is a good example of the formulation of new feedback loops that help build control mechanisms, thereby facilitating development of sustainable agriculture. One of the prerequisites for maintenance of a sustainable agricultural system is the existence of negative feedback loops in which outputs (e.g., environment threats) influence the inputs (e.g., use of particular production means); otherwise, the system loses its integrity and may transform to another state. A network of negative feedback determines the resilience of the system

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to environmental disturbances. Distortion of landscape functions that may be caused by farming intensification and lead to altered energy fluxes and organic matter cycling patterns should either (1) be counteracted by mechanisms (negative feedbacks) that diminish inputs that cause threats or (2) be controlled by rearranging the system structure in such a way that the distortion itself is arrested. It is important to note that because the landscape distortions are caused by farmers, the elaboration of negative feedback mechanisms should encompass both environmental and societal components of the landscape. The development of the new CAP has relied mainly on the first method to counteract increased environmental deteriorations. The CAP reform marks an important step toward implementing a sustainable agriculture, thereby enabling the transition from identification of a crisis to its control. In other words, it is a transition from recognizing the causes of environmental threats and observing their impact on the economy or living conditions of the general public, which stimulates calls for the administration to take action, to undertake effective measures to control the actual threats. This transition was realized by involvement of administrative structures of society in the control of threats. The sooner we understand that scientific recognition of environmental impacts, public pressure on administration to eliminate such threats, and the forging of control regulations by decision makers are a normal part of learning to deal with crises, the easier it will be to design policies of sustainable development. The efficiency of such control mechanisms depends very much on the elaboration of the ways of opening channels of communication between those who understand the process in question and the general public and decision makers. The environmental problems created by agriculture are handled within the context of the new CAP mainly by imposing restrictions on agricultural activities — for example, the Nitrates Directive issued by the Commission of the European Communities (CEC) in 1991 — or by protection of biota as well as habitats against human interferences — for example, the Birds Directive issued in 1979 or the Habitats Directive of 1992. Thus, the concerns are directed toward mechanisms constraining intensity of inputs that are causing the threat (elaboration of negative feedback loops concept). Implementation of the Nitrates Directive has been rather unsuccessful (Com 1999). One reason is probably that the Nitrates Directive does not mandate compensation to farmers because of the “polluter pays” principle, which requires farmers to observe good agricultural practices without payment. This situation demonstrates that the efficiency of negative feedback loops that encompass societal structures is to some extent tied to the exchange of capital. The main restrictions of the Nitrates Directive are connected with further elaboration of limits on amounts of fertilizers used and imposed requests concerning delimitation of areas sensitive to leaching. In addition, special thresholds for application of inorganic and organic fertilizers and modified tillage technologies that are proposed should be observed. Both the Birds and Habitats Directives provide a basis for setting up the EU program on nature conservancy (Natura 2000) consisting of the establishment of a refuge sites network, where bird protection measures are implemented and certain agricultural activities that threaten the biota are restricted.

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SUSTAINABLE AGRICULTURE The most important achievement of the new CAP is its recognition of landscape properties for the sustainable development of agriculture (Com 1999). The study of landscape properties leads to disclosure of links between natural and societal processes that change landscape structures and also provide opportunities for economic activities. A landscape has multifunctional characteristics that make it significant as a material object but also creates a sensitive relationship between humans and their environment. The sustainability concept is based on three main pillars — economic, social, and environmental — which should be balanced in such a way that change in one pillar does not undermine the whole system. Thus, production increases should complement a higher standard of life and also sustained improvement in the quality of the environment. Maintenance of such a situation could be achieved by two systems of management. The first system relies on development of more environmentally friendly technologies that can be used when production is increasing. The second system focuses on building buffer capacities in the system that could neutralize any negative side effects of the increased production. The codes of good agricultural practices describe ways to introduce environmentally friendly technologies, but enforcement requires administrative regulations. Maintenance of good soil quality and soil fertility can provide long-term economic gains. Cultivation technologies that aim to increase storage capacity of soil and to preserve or improve its physical, chemical, and biological properties are of the utmost importance for successful development of sustainable agriculture. In the arsenal of available technologies one can include diversified crop rotation patterns, minimizing exposure of bare soil, which constrains erosion rates and simultaneously prevents accumulation of hazardous biochemical compounds (e.g., phenolic acids) that inhibit growth of cultivated plants (Ryszkowski et al. 1998). Plowing green manure into soil as well as frequent application of farm manure restores and preserves the organic matter in soils that have the most importance for sustaining soil fertility over long periods. Increased integration of crop and animal production within the farm, leading to tight recycling of nutrients and therefore less loss of nutrients to ground and surface water reservoirs (Granstedt 2000), is another option for farm-level control of environmental problems. Integrated methods of pest and disease control can reduce the use of pesticides and no-till technologies and can restore the physical and chemical properties of soils as well as stimulate rich communities of soil microorganisms. Nevertheless, as shown by Ryszkowski and Jankowiak in Chapter 2, all those technologies cannot eliminate problems caused by agriculture; they can only reduce them. Agroecosystems can be managed for simplification of their structure which facilitates higher yields but also decreases efficiency of their recycling processes and stimulates diffuse pollution in an entire region. Water and microclimate management issues must also involve very large areas to be effective. The same can be said with regard to protecting biodiversity. The effective introduction or rearrangement of linear or clump elements, such as groves, shelterbelts, stretches of grasslands, mid-field ponds and wetlands, riparian vegetation strips, and stone wells, all of which function as biogeochemical barriers,

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can influence the rates and direction of basic processes in the landscape, but can be accomplished only on a scale much larger than a single farm. This analysis leads to an important conclusion. The farm is an autonymous or self-sufficient unit with respect to its economic processes. But a farmer’s sovereignty over the natural processes is not great. Thus, there is a considerable functional discrepancy between a farm as an economic enterprise and its role in environmental protection programs. The activities within the farm may be on too small a scale to curb environmental deterioration. This does not mean, however, that environmentally friendly technologies are not important. On the contrary, they are very important, but their execution needs to be coordinated on a large spatial scale, including many farms, to achieve significant impact on a range of the natural processes in question. This situation calls for coordination of farmers’ activities at the landscape level. In addition, the introduction of biogeochemical barriers may interfere with economic benefits obtained by individual farmers; therefore, the decision on their optimal localization should be undertaken from the perspective of protecting the interests of all of society (the societal pillar of sustainability) rather than those of the individual farmers. The problems and conflicts arising in such situations were analyzed well by Hardin (1968).

LANDSCAPE MANAGEMENT IN DEVELOPMENT OF SUSTAINABLE AGRICULTURE The problems of spatial layout and design of various landscape elements can be addressed by spatial planning, which recently became one of the new dimensions of the EU policies of development. In order to reconcile the social and economic claims for spatial development with an area’s ecological and cultural functions, the program for the European Spatial Development Perspective (ESDP 1999) was proposed by ministers responsible for spatial planning in the EU member states. With respect to agriculture, this political initiative aims not only at delimiting regions having different production intensity or specific problems (such as excessive specialization or concentration of production) but also indicates the need for recognizing the interactions between agriculture and other sectorial activities in order to find synergies that may result. The proposed ESDP policy based on those findings should lead to strategies for minimizing conflicts between different land users, for example between farmers and nature conservationists, by implementing the Natura 2000 program on a wide network of protected areas. According to the ESDP, “a broader land-use policy can provide the context within which protected areas can thrive without being isolated.” Recognition of the importance of spatial dimensions in the relationships between economic and societal aspects introduces broader possibilities to manage the negative effects of development. These negative effects can be combated with suitable regional planning that minimizes conflicts (ESDP 1999). Thus, the policy incentives mentioned above provide new options to moderate conflicts between sectorial activities and the social well-being of the people.

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One can expect that the development of the ESDP policy will also influence the CAP expanding arsenal of measures for controlling environmental deterioration from agricultural intensification. The discussion of the control measures of environment deterioration proposed by the CAP, presented at the beginning of this chapter, showed that regulations rely mainly on restricting the sources of environmental threats (e.g., Nitrate Directive). Methods for building resistance to threats at the landscape level are still not a broadly used operational option, although Recommendation Nr. R(94)6, on sustainable development and use of the countryside with a particular focus on safeguarding wildlife and landscape (issued by the Council of Europe in 1994) proposes structuring landscape with hedges, ponds, and buffer zones. The aim of those activities is the stimulation of natural processes of landscape self-purification and control of diffuse pollution. Nevertheless, to date, there is no EU directive for enhancing landscape resistance to environmental threats. Such regulations will reinforce the arsenal of current regulations with a new category of measures that allow some intensification of production with side effects that could be neutralized by natural processes enhanced through landscape management. This new approach to control of environmental threats has a very important implication for the development of sustainable agriculture. More intensive agricultural production results in higher yields, which in turn provide opportunities for improved economic revenue. This aspect is of special interest to farmers for whom a positive link between income and environmental threat control measures would be more persuasive than would proposals restricting production. This statement is supported by the results of a census carried out by the Research Center for Agricultural and Forest Environment in Poznan´ , Poland. Farmers were asked to identify what they considered the most important environmental threats. The majority indicated those threats that directly impact yields, while those threats with an indirect effect on production were either neglected or recognized only by those farmers with a higher education. For example, 71% of 168 respondents clearly recognized effects of drought, which decreased yields, while only 7% indicated existing water pollution problems as important. It seems, therefore, that control measures for environmental deterioration that do not restrict production and revenue constitute a better strategic approach than those that establish such restrictions. The crucial point for applying a landscape approach to controlling environmental degradations is that side effects of agricultural production intensification should not exceed the buffering capacities of the landscape. Observation of that condition requires proper education of farmers and development of extension services qualified in landscape ecology. Landscape ecologists showed some time ago that the mosaic structure of landscape can stop disturbances (e.g., Forman and Gordon 1986). The review of recent ecological studies presented in this book clearly shows that many natural processes could be modified by a mosaic landscape structure. One of the most important results of those studies is the indication that stands of permanent vegetation can modify heat balances and water cycles in the countryside. Trees, for example, are efficient ecological water pumps increasing evapotranspiration rates and at the same time slowing surface runoff. The complicated structure of a tree stand can modify microclimatic conditions of adjoining fields largely because of its effects on wind velocity.

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Cultivated fields can be considered “landscape ovens,” heating air, which could even influence mesoscale air circulation due to increased rates of heat convection. Shelterbelts in a simplified agricultural landscape are one of the best tools by which one can manage not only microclimatic conditions but also water cycling in the landscape. The tradeoff between those processes depends on the kind of biogeochemical barrier, its structure, and the pattern of the network. A network of biogeochemical barriers can also efficiently control diffuse water pollution if combined with management practices aimed at the removal of accumulated plant debris, which rapid decomposition under favorable microclimatic conditions can turn a biogeochemical barrier from a sink to a source of contaminants. The biological processes of nutrient uptake, denitrification, assimilatory reduction of nitrates, and decomposition of organic matter play very important roles in the process of nitrogen cycling in the landscape. It seems that processes of biological recycling within the biogeochemical barrier play a substantial role in processes that determine the control of the barrier for modification of adverse matter cycles in landscapes. A mosaic of refuge sites in the agricultural landscape houses much richer and more diverse plant and animal communities than does a uniform landscape that is composed of large cultivated fields and that largely lacks other nonagricultural landscape components. Analyses indicate that a more diversified landscape structure stimulates the appearance of a larger number of taxa as well as greater density and biomass of the animal communities. In nonarable habitats sheltered by the biogeochemical barriers, for example, mid-field ponds separated from fields by meadows or hedges, even protected or rare species can thrive in the agricultural landscape. The success of biodiversity protection by the biogeochemical barriers depends on farming operations. Thus, a tradeoff between farming intensity and pattern of refuge sites must be established in order to reconcile agricultural activities with biodiversity protection. Elaboration of the methods of decision making in regard to proposed land uses constitutes the important step reported in this book to communicate landscape ecology achievements to policy makers. Development of computer tools to model the environmental consequences of proposed land-use changes can facilitate the incorporation of landscape ecology guidelines into agricultural policies. The same is true for elaboration of operational guidelines for managing biogeochemical barriers, e.g., instructions on management practices for shelterbelt maintenance. Such modeling can also help efficiently translate landscape ecology into common practice, such as attempts to introduce riparian forest buffers into the U.S. program for water quality protection.

CONCLUSION Trends in the development of agricultural policies, as shown in the example of the EU common agricultural policy, as well as the achievements of landscape ecology, described above, indicate that in the future one can expect a merging of those fields of human activities to provide more efficient ways to develop sustainable agriculture.

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It seems likely that agrolandscape ecology will be an important discipline that will influence agricultural practices in the 21st century. These tasks are not easy to accomplish. First, for example, restricting contamination of water reservoirs and building environmental resistance require considerable money. Hence, poor farmers will have difficulty implementing effective environment protection programs. Second, farmers are still not sufficiently educated to make profitable use of the achievements of contemporary ecology to restrict nonpoint pollution, save water, or control erosion processes through diversifying landscapes. Environmentally friendly cultivation technologies recently proposed by various proponents of alternative agriculture indicate a number of activities that are very sound from an ecological point of view. But the efficiency of environmental protection of rural areas could be enhanced even further if field practices could be supplemented by structuring landscapes with various biogeochemical barriers, which would not only augment control of nonpoint pollution, save water, and modify microclimatic conditions but also conserve biodiversity.

REFERENCES Com 1999. Direction toward sustainable agriculture. Commission of the European Communities. Brussels. 30 pp. ESDP. 1999. European Spatial Development Perspective. Office for Official Publications of the European Communities. Luxemburg. 82 pp. European Environment Agency. 1998. Europe’s Environment: The Second Assessment. Elsevier Science Ltd. Oxford. 293 pp. Forman R. T. T., Godron M. 1986. Landscape Ecology. Wiley & Sons. New York. 619 pp. Granstedt A. 2000. Increasing the efficiency of plant nutrients recycling within the agricultural system as a way of reducing the load to the environment — experience from Sweden and Finland. Agric. Ecosys. Environ. 80: 169–185. Hardin G. 1968. The tragedy of the commons. Science 162: 1243–1248. Ryszkowski L., Szajdak L., Karg J. 1998. Effects of continuous cropping of rye on soil biota and biochemistry. Crit. Rev. Plant Sci. 17: 225–244. Stanners D., Bourdeau P. 1995. Europe’s Environment. European Environment Agency. Copenhagen. 676 pp.

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Index A Abandoning cultivars, 188 Aboveground insects, mosaic landscape, 203 Accipter gentilis, in Turew shelterbelts, 208 Acidification, agriculture intensification, 16 Active surface defined, 35 radiation balance, 32 Aerial photography, forest islets, 324 Afforestation, See also Forest islets, Forests aesthetic/recreational land value, 304 ammonium cations, 123 anti-erosion measure, 303 biodiversity preservation, 308 bird habitat, 207, 308 clear cutting, 310 crop protection, 310 decreased, 306 design and management guidelines, 307–311 early recognition of benefits, 300 economics, 310, 311 evapotranspiration, 302 extreme weather phenomena, 303 factors affecting success, 305 Hungary, 305 insect habitat, 308 landscape simplification, 258 management, 299–312, 321 mid-field, management of, 304–311 networks, 19 nitrogen pollution, 119–122 past rationale for, 304–305 persistence, 309–310 plant diversity, 193 plant litter and nitrogen leaching, 133–134 plant species composition, 309 protective role, 299 providing for specific functions, 307–308 recommended by Chlapowski, 300

refuge habitats, 300, 304 set-aside programs, 300 slope-width relationship, 308 solar energy conversion, 23 south Romanian plains, 305 tree age and bird density, 208 tree species, 300, 307 underestimation of problems, 305 water, 302 wet conditions, 308 wind-breaks, 308 Agricultural landscape analysis, functional approach, 1–7 animal abundance and diversity, 199–209 animal community impoverishment, 197 as buffer, 147 biological control of pests, 204 diversification and plant diversity, 194 Europe, 220 increasing without ecological consideration, 67 “leakiness,” 147 management, 10, 333–334 protection in east and central Europe, 305 rural settlement, 259 sustaining, 333 Agricultural revolution, 10 Agricultural subsidies, European Union, 290 Agriculture, See also Agriculture intensification 21st century challenges, 332–337 beginnings, 10 code of best practices, 343 cultivation effect on biomass, 12–17, 194–199 development of, 9–24, 112 effect on Protozoa, Enchytraeidae, Collembola, 198 energy input, 11 enforcing codes of good practice, 343 environmental consequences, first recognized, 10 farm as autonymous unit, 344

349

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feedback mechanisms, 3–4 history of, 10–12, 253 impact on landscape, 12–17 industrialization, 12 integrated, 17 intensive input, 332 mechanization, soil erosion, 265 modern practices, 332 objectives compared to nature protection, 341 policies, trends, 347 resistance ability, 345 shelterbelts, 306 single crop farming, 332 slash-and-burn, 11 sustainable development 10, 331, 342 Agriculture intensification, 112 agroecosytem structure, 13 building resistance to environmental threats, 345, 346 effects of, 185–186, 301, 341, 342 European Union environmental threats, 14 greenhouse gases, 13 insect size relationship, 197 soil salinization, 16 studies on effects, 301 Agriculture research fragmentation, 334–335 Agro-ecological Park, Poland, satellite image, 319 Agroecology, 331–337 Agroecosystems, 13 Agro-industries, Northern Parisian Basin, 267 Agrolandscape approach to agricultural management, 333–334 Agrolandscape ecology, 331–337 Agrolandscapes, See Agricultural landscape, Rural land use Agrometeorological index, 34 Agronomy, integrating with ecology, 335 Air heating, plant cover effects on energy, 90 Albedo, 31 Alfalfa heat balance structure component modeling, 44 water balance with/without shelterbelts, 99 Algae, 161 Allochthonous organic carbon, sources, 161 Alma-Ata, heat balance component measurements, 37 water balance structure studies, 76 Amberlite XAD resin series, 164 Ammonia volatilization, 127 Ammonia nitrogen assimilation, 125 soil sorption, 115 Ammonium controlled by biogeochemical barriers, 127 leaching into ground water, 127

Ammonium cations concentrations in afforestations, 123 compared to nitrates, in Turew, 121 Anatolia, Turkey, beginning of agriculture, 10 Animal abundance, agricultural landscape, 199–209 effect of land-use change, 202 Animal communities, See also Refuge birds in Turew, 206–209 diversity, agriculture landscape, 199–209 effect on agriculture, 194–199 energy dissipation estimates, 196, 197 herbivore presence in meadow compared to wheat, 198 invertebrate elimination factors, 198 landscape structure influence, 199 migration between ecosystems, 197 percent of total organic matter, 194 refuges and cultivated fields, 202 reproduction rate among agriculture activity, 196 shelterbelts, colonization, 205 Anser anser in Turew shelterbelts, 208 Aphids, 198 overwintering in shelterbelts, 204 Apoidea, Turew, 202 Aquatic ecosystems metal tocixity and transport, 177 restoring, 154 Areal heat estimation, 35 Asikli, beginning of agriculture, 10 Assimilatory nitrate reduction, 125, 346 Assimilatory reduction, 129 Atmosphere, vegetation interaction, 32 Atmospheric changes, 30 Atmospheric water, circulation of, 60 Atrazine, Northern Parisian Basin surface water, 273–274 Australia, precipitation and plant cover, 86 Austria ground water pollution, 16 nitrate concentrations,112 Autochthonous organic matter, sources, 161 Avian fauna, See Bird communities

B Badgers, in Turew shelterbelts, 208 Bare soil, minimizing, 344 evapotranspiration, 43 Belgium ground water pollution, 16 nitrate concentrations, 112

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Belowground fauna, 197 Biodiversity, See also Animal communities, Animal diversity afforestation, 304, 308 agricultural intensification, 13 agricultural landscape, 199–209 agrolandscape perspective, 333 animal migration between ecosystems, 197 biogeochemical barriers, 301 effect of water deficits, 16 field margin structure, 239 herbivore presence in meadow compared to wheat, 198 management in agricultural landscape, prospects, 209–210 mosaic landscape, 23, 185–211, 206, 346 pesticides in Northern Parisian Basin, 274 plant diversity, 210 shelterbelt management, 310 species dispersal properties, 206 strategy, integrating with social/economic sectors, 209 forest islets, 318, 324 Biodiversity Convention, 186 Biogeochemical barriers, 18, 19, See also Afforestation, Buffer zones, Field margins, Grasslands, Meadow, Plant cover, Riparian buffers, Shelterbelts adjusting to afforestation functions, 307 ammoniun ion control, 127 control mechanisms, 21 diffuse water pollution, 346 dissolved organic matter concentrations, 172 Europe, 301 humic substance concentrations, 172 nitrate, 131, 137, 138 nitrogen pollution, 119-122, 130 nitrogen processing, 122–129 percentage of nitrate concentration in field, 133 phosphate and nitrate output from watersheds, 131, 160 plant litter and nitrogen source, 134 pollution control, 301 processes determining functions, 301 roles, 301 shelterbelts and woodlots, 301–304 slope and barrier efficiency, 120 water-purifying functions, 5 width for pollution control, 131 Biological diversity, See Biodiversity Biomass decomposition, 163 energy expense in simplified plant cover, 196 maintenance, wheat field compared to meadow, 196

351

mean levels across countries, 201 Biosphere-atmosphere mass and energy exchange, 32 eddy covariance method, 33 Biota refuge habitats, 18, 19, See also Animal communities, Refuge Bird communities afforestation habitat, 308 density and tree age, 208 diversity factors, 207 farmland, decline in U.K., 222 utilization of field margin, 222 Turew, 202, 206–209 young shelterbelts, 208 Birds Directive (CAP), 343 Black locust in afforestations, 300 Boars, in Turew shelterbelts, 208 Bocage, 300 Bowen ratio, 34 negative values, 37 values in dry and wet years, table, 45 Bristol, U.K., field margin study, 223 Buffer zones, See also Biogeochemical barriers, Riparian buffers agriculture landscape as, 147 Bullfinch, utilizing field margins, 222

C Cadmium, complexing ability, humus, 177 Canadian Prairie Farm Rehabilitation Administration, Shelterbelt Centre, 303 Cantabrian Mountains, 300 CAP, 13, 112 agriculture and environmental protection integration, 17 Birds Directive, 343 codes of good agricultural practices, 343 control of environmental threats, 342, 343 ESDP, 345 feedback loops, 342 ground water pollution, 16 landscape functions, 343 Nitrates Directive, 343 overproduction effects, 14 reforms, 14 set-aside program, 300 Capreolus capreolus, in Turew shelterbelts, 208 Carbon dioxide evolution from shelterbelts (table), 128 shelterbelts (Turew), 127 Carex davalliana, 191 Carpatian Mountains, 300

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Catalhöyük, beginning of agriculture, 10 Catalpa, in afforestation, 300 Catchment, 68, 69 CBI, 151 Central Europe, See also individual countries economic/political reform and agricultural landscape programs, 305 water resources, 59 Cereal cultivation, effect on animals, 198, 202 Cessieres, France water balance structure studies, 76 heat balance, 37, 39 Chemical leaching, 13, 119–122 control mechanisms, 5 controlled with vegetation strips, 21 effect of precipitation, 121–122 organic matter cycling, 4 Chemical volatilization, 13 China, beginning of agriculture, 10 Chlapowski , General Dezydery, 19, 115, 321 recommendation of afforestation, 300 Class differentiation, 10 Clear cutting, 310 Climate water balance structure, 75–81, 101–104 water cycling, 6 worsening water conditions, 65 Coleoptera, Turew, 201 Collembola, agriculture effect on, 198 Colorado beetles, 198 Common Agricultural Policy, See CAP Complex stability, copper, lead, and cadmium, 178 Congo, precipitation and plant cover, 86 Conservation practices, riparian buffers, 150 Copper, 178 concentration, Turew, 175, 176 Corn bunting Turew shelterbelts, 208 utilizing field margins, 222 Corridor, defined, 146 Corvus corax, in Turew shelterbelts, 208 Cranes, in Turew shelterbelts, 208 Crataegus bignonioides, 300 Crataegus monogyna, 300 Crataegus oxyacantha, 300 Crop protection development, 310 Crop rotation, 11 diversified, 344 effect on biodiversity, 186 simplified, limiting weed diversity, 188 Crop yields, effect of shelterbelts, 306 Cross pollination, restricting with shelterbelts, 303 CRP, 151, 152 CS-CRP, 152 Cultivar abandonment, 188

Cultivated fields, influencing mesoscale air circulation, 346 Cultivation effect on biomass, 195 environmentally friendly, 136 soil erosion, 265 Czech Republic, agricultural landscape protection, 305

D Decomposition, no-till agriculture, 333 Dendrocops medius, in Turew shelterbelts, 208 Denitrification, 131, 346 Denmark ground water pollution, 16 wetlands disappearance, 112 Dew, 86 Diffuse pollution, 16, 18, 111–139, 300, 344 afforestation, 302 biogeochemical barriers, 19 contributing factors, 112 control guidelines, 135 environmentally friendly cultivation methods, 136 ground water, 16 landscape management control, 135–138 nitrogen control and landscape management, 129–135 riparian buffers, 113, 136, 148, 154 shelterbelts and meadows, 111–139 soil organic matter, 136 U.S. policies, 135 Wielkopolska region, fertilizer use, 258 Dissimilatory nitrate reduction, 125 Dissolved organic carbon, 160 effect of meadow width, 173 humic substances, 164 measuring, 160–161 Dissolved organic matter effect of meadow width, 172 excreted by macrophytes, 163 heavy metals, 177 seasonal concentrations, 163 Dissolved oxygen, riparian buffers, 152 Distillation, 86 Diversified crop rotation patterns, 344 Domestic animals, establishing riparian buffer functions, 151 Dragon fly, Turew, 201 Drainage, 6 Drought, precipitation variation, 65 Dynamic equilibrium, 319

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E Earthworms, 197 agriculture effect on, 198 in Turew, 199, 202 no-till agriculture, 333 Ecological corridors, 19 Ecological engineering, 2 Ecology, integrating with agronomy, 335 Economic sustainability, riparian buffers, 150 Ecosystem classification, 335 Ecotone, defined, 220 Eddy covariance method, 33 Eddy flux determination, 33–34 Egypt, beginning of agriculture, 10 Emberiza hortulana, in Turew shelterbelts, 208 Enchytraeidae agriculture effect on, 198 Turew, 202 Endoaquolls, 115 Energetic water demands (EWD), 94 Energy advection, shelterbelts, 44 Energy flux land-atmosphere exchange, 31 link to matter cycling, 65 modeling, 30 net radiation, 32 vertical, 23 Energy input characterizing, 31 ratio to output, 11 Energy utilization, efficiency, 79–80 England decreased afforestation, 306 field margin study, Bristol, U.K., 223 nitrate concentrations, 112 Environmental costs, incorporating into rural development, 18 Environmental degradation, resistance to, 19 Environmental impact modeling, 282–283 Environmental processes, modeling, 34 Environmental protection controlling threats, nonproductive landscape components, 19 costs, 18 forecasting threats, 6 landscape level, 18 resistance to degradation, 19, 345, 346 threats from agriculture, 341–342 Environmentally friendly practices, 344 Erosion, 13, 302, See also Soil ersion afforestation, 303 bare soil, 344 biogeochemical barriers, 301 control, 19

establishing riparian buffer functions, 151 lack of plant cover, 14 mosaic landscape, 23 precipitation variation, 65 ESDP, 345 Europe, agricultural landscape and area, 220 European Spatial development Perspective (ESDP), 345 European Union, See also individual countries Common Agricultural Policy (CAP), 13 subsidy system, 290 Eutrophication reducing at landscape scale, 334 water quality and treatment, 111 Evaporation, 60 from bare soil, 84 Evapotranspiration, 72–73, See also Latent heat flux affected by plant cover, 87 bare soil compared to forest, 43 birch and pine, 130 comparison of agricultural landscapes, 100 during growing season, 22, 100 effect of increased temperatures, 101 energy, 78, 80 ensuring adequate, 96 estimating, 30, 69 forests, 88 heat balance equation, 32 herbaceous plants, 346 humidity effects, 77 Hungary, 60 intensity and solar energy flux, 79 plant cover and weather, 78–79 plant cover root development, 88 ratio to precipitation, Turew, 90 reducing, 100 relationship with plant cover structure, 4 seasonal course and plant cover importance, 88, 89 soil factors determining, 85 stability in overgrown soil, 82 sugar beet compared to stubble field, 78 trees, 302, 346 Wielkopolska region, 73 EWD, 94

F Falco subbuteo, in Turew shelterbelts, 208 Farm autonomy, 344

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LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Farm machinery, 13, See also Agricultural intensification, Agricultural mechanization, 13 Farm production, 17, integrated with environmental protection, 17 Farm size changes, 112 Farmland wildlife, See Birds, Insects, Mammals, Wildlife Fecal coliform, riparian buffers, 152 Fertile Crescent, beginning of agriculture, 10 Fertilizer agriculture leakiness, 147 biochemical barriers, 19 field margins, 240, 242 green manure, 344 ground water quality, 342 industrial, 11 input and nitrogen output, 116–118 input, reducing, 333 limiting weed diversity, 188 mineral, 11 mineral nitrogen in soil, 124 mosaic landscape, 18 Northern Parisian Basin, 266, 272, 273 organic content depletion, Wielkopolska region, 255 ponds for matter cycling, 19 riparian buffers, 150 stabilization versus reduction, Northern Parisian Basin, 275 stock and crop farming, 257 surface water, Northern Parisian Basin, 273 watersheds, 159 Ficedula hypoleuca, in Turew shelterbelts, 208 Field boundaries, 220–232 Field margins, 221 afforestation, 303 biodiversity, 222, 225, 229, 239 bird utilization of, 222 classification in the bocage, 236, 237 ecological impact of enlarging, study methods, 223–224 effect of fertilizer and herbicide, 240, 242 fertilizer/herbicide impact on sown flora, 229 flora development, 227, 229 flora diversity, 225, 234 ground beetle dispersal, 241 herbaceous plant diversity, methods for studying, 226 impact on fauna of enlarging margin, 230–231 impact on flora of enlarging margin, 227–229 insects, 241 inter-plant interactions, 240 landscape scale studies, 225 managing, 242

overwintering of invertebrates, 231 pests and disease, 242 sown margins, 243 sown perennials, 242 sown strips, 240–241 spatial behavior of ground beetles, 232–234 structural diversity, 243 traditional perspective of, 222 weed management, 241 Field structure, 258 Flood precipitation variation, 65 riparian buffers supplement, 148 Forest islets as land units, 319 biodiversity, 318, 324 remote sensing, 322, 326 Forests energy for evapotranspiration compared to wheat, 90 evapotranspiration, 43, 88, 90 latent heat flux, 42 management, 321 net radiation, 41 precipitation, 86 runoff, 87 sensible heat flux, 42 water retention, 96 Wielkopolska region, effect of clearing, 253 France, See also Northern Parisian Basin, Picardy, Soissonnais agricultural changes and reforms, 275 agricultural production, 263 decline in hedgerows, 306 ground water pollution, 16 nitrate concentrations, 112 sugar industry, 267 wheat yield, 266 Fulvic acids, in ground and surface water, 174, 175

G GCM model, 34, 59 Gentiana pneumonanthe, 191 Geological diversity, 5 Geomorphology, simplified because of mechanization, 13 Georgia (U.S.), riparian forest buffers, 152 Germany Göttingen, field margin study, 223 ground water pollution, 16 Hannovermünde, 305

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INDEX

355

Main River catchment, heat and water balance structure, 48 nitrate concentrations, 112 Gleditschia triacanthos, 300 Global hydrologic cycle, 58 Global radiation, 31 Global warming, 101 Glossudalfs, physical and chemical characteristics, 114 Goshawk, in Turew shelterbelts, 208 Göttingen, Germany, field margin study, 223 Grain crops, runoff, 87 Grasslands control of nitrogen pollution, 119–122 erosion control, 19 loss of, Poland, 16 seminatural, plant diversity, 192 water quality control, 136 Grass margins, 241 Gray lag goose, in Turew shelterbelts, 208 Gray partridge, utilizing field margins, 222 Great gray shrike, in Turew shelterbelts, 208 Greenhouse gases agricultural intensification, 13 long wave radiation, 31 Ground beetles, dispersal, 241 Ground water bound lead and copper concentrations, 177 chemistry of, 301 diffuse pollution, 16 dissolved organic matter, 160, 161, 163 fertilizer use and quality, 342 humic substances, 164–165, 171–172 level and water management, 81 nitrogen contamination, 334 pollution control, 113 pollution, European Union policies, 135 polypeptide concentrations, 170 polysaccharide concentrations, 170 seasonal concentrations of humic substances, 166 water table depth and afforestation, 308 zinc concentration, Turew, 175 Grus grus, in Turew shelterbelts, 208

H Habitat diversity, See also Mosaic landscape plant species richness, 190 Habitat loss, conventional tillage, 332 Habitat moisture, 80 Habitat refuge, monocultures, 332 Haies, 300

Hannovermünde (Germany), 305 Hapludalfs, physical and chemical characteristics, 114 Harpalus rufipes, in field margins, 233 Hawthorn, in afforestation, 300 Heat advection, 69 Heat balance equation, 32 Heat balance structure change as function of landscape structure, 44 climatic conditions, 39–40, 48–53 components, 31–32 daily course, illustrated, 36 daily courses and crop differences, 40 estimation, 34 measuring and modeling, 32–35 modeling, 44 seasonal values, 41–48 shelterbelts, illustrated, 46 daily dynamics, 35–41 describing environmental conditions, 31 equation, 32 estimate methods 4 factors, 35 impact of landscape structure (table), 39 land-use influence, 52 Main River catchment, 48 managing with shelterbelts, 43 plant cover, 29–53, 37, 39 seasonal courses, 49 turbulence components, 33 vegetation type, 48 Heat flux, measuring, 33 Heavy metals, See also Metals, and individual metals bonds with organic compounds, 177 concentration in natural waters, 174–177 effect of humic substances, 173–174 geochemical mobility, 160 mean concentrations of forms, 179 Hedgerows, 300, See also Field margins, Biogeochemical barriers Cantabrian and Carpatian Mountains, 300 decline of, 306 extreme weather, 303 Herbicides effect in field margins, 240, 242 limiting weed diversity, 188 Herbivores, meadow compared to wheat field, 198 Heteroptera, in Turew, 201 Heterotrophic systems, 336 Hierarchical systems theory, 20 Hobby, in Turew shelterbelts, 208 Honey locust, in afforestation, 300 Human impact on environment, 9–12 Humic acids heavy metal as stable complexes, 177

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356

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

in ground and surface water, 174, 175 Humic substances, 160 aquatic environments, 164 aerobic conditions, 167 binding ability toward heavy metals, 177, 178 concentration and precipitation, 165, 167 concentrations during dry conditions, 170 effect of meadow width, 171–172, 173 effect on heavy metal speciation, 173–174 eutrophic lake concentration, 167 ground water, 166 metal ions associated with, 177 mid-field ponds, 170 oxidation, 178 recovering, 164 seasonal concentrations, 166, 167 separation into humic and fulvic acids, 174 surface water, 167 Humus nitrogen storage compared to wood, 129 resources augmentation, 17, 19 Hungary agricultural landscape protection, 305 climatic water balance, 60 runoff coefficient, 61

I IALE, 2 Industrial fertilizers, 11 Insect communities, comparing among ecosystems, 200 Insects aboveground, impoverishment, 200, 201 abundance and age of shelterbelts, 206 adaptation to environments, 201 afforestation habitat, 308 Colorado beetles, 198 diversity in mosaic landscape, 202 dragon fly, Turew, 201 field margins, 222 flying, distribution in Turew, 201 ground beetle dispersal, 241 hibernating in young and old shelterbelts, 206 monoculture, 332 overwintering in field margins, 231–232 range of field penetration, 204 refuge habitats, 202 spatial behavior of ground beetles, 232–234 spiders, 198, 202 winged, agricultural effect on, 198 Integrated agriculture, 17 Integrated land development, 278

Integrated models, landscape modeling, 284 Integrated weed management (IWM), 187 International Association for Landscape Ecology (IALE), 2 International Union for Conservation of Nature and Natural Resources, 191 Inter-plant interactions, field margins, 240 Invertebrates, factors leading to their disappearance, 198 Iowa, U.S., riparian forest buffers, 152 Iron, soluble, 177 Irrigation, soil salinization, 16 Italy aboveground insect populations, 200, 201 afforestation, 304 ground water pollution, 16 nitrate concentrations, 112 IUCN species survival evaluation, 191 IWM, 187

K Kazakhstan, water balance structure studies, 76 Kujawy region, Poland, 60 precipitation variation, 65 Kursk, Russia heat balance component measurements, 37 water balance structure studies, 76

L LAI, 86 Lakes, organic matter content, 161 Land owners, conflicting interests, 345 Landscape, See also Agricultural landscape, Mosaic landscape change, 15 defined 20, 146 modeling spatial aspects, 284–285 thermal conditions and water effect, 64 Landscape approach, 17 Landscape diversity, 17, 18, See also Mosaic landscape biodiversity, 209 management, 18 pattern changes, 248–262 Landscape ecology, 333 defined, 1 geographical approach, 2 Landscape function, feedback mechanisms, 3

0919 Index Frame Page 357 Wednesday, November 21, 2001 2:32 PM

INDEX

Landscape management, 10, 67 afforestation, 299–312 controlling environmental threats, 17–19 field margins, 239–240, 242 for biodiversity, 209 intensity of, 146 landscape approach, 23 nitrogen pollution control, 129–135 pollution control guidelines, 135 reconciling nature and human activity, 12 riparian buffers, 149 sustainable development, 20–24 Landscape models, 283–284 Landscape Park im D. Chlapowskiego, seasonal water conditions, 92 Landscape scale, 3 Landscape simplification, 186 Landscape structure diversification and water balance structure, 78 diversity and animal persistence, 199 effect on chemical dispersion, 118–119 effect on precipitation, 71 elements, 146 heat and water balance structure change, 44 net radiation partitioning, 43 Landscape uniformity, 341 Land unit choice of samples for remote sensing, 323 defined, 318, 319 biodiversity, 318 sampling, transect, 325 Land-use, See also Land-use change, Land-use modeling agricultural politics, subsidy change, 290–292 assessing environmental impact, 282–283 decision making, 53, 347 influence on heat and water balance structure, 52 models for optimization, 284 nature protection, 186 net radiation partition, 32 water balance structure, 86–91 water runoff, 74 Wielkopolska region, 253–257 Land-use change, 20, 278, See also Land-use, Land-use modeling, Land-use planning, Rural land development climate effects, 23 cultivations for foodstuffs, 268 development in land use, 282 difficulty assessing impact, 279 effect on animal communities, 202 effect on water condition, 67 energy fluxes, 48 goals, 289 modeling impact, 277–294

357

planning, decision making, 279, 280 regional evaluation, diagram, 281 Land-use modeling, 277–294 agricultural politics, subsidy change, 290–292 approaches, 283–284 assessing environmental impact, 282–283 biotic components and processes, 284 collecting data, 283 congruent environmental goals, 289 development in land use, 282 divergent goals, 289 landscape biocoenoses, 284 landscape processes, 283 land-use optimization, 284 lateral processes, 284 MODAM, 285–294 multi-objective optimization (example), 285–294 multi-optimization model, 286–294 simulations for study area, 289 spatial aspect modeling, 284–285 spatial data and spatial design, 283 stepwise models, 284 Land-use planning alternatives in decision making, 290 decision making (example), 285–294 environmental protections, 285 Lanius collurio, in Turew shelterbelts, 208 Lanius excubitor, in Turew shelterbelts, 208 Larch, afforestation, 307 Latent heat flux, 32, See also Evapostranspiration climate zone differences, 77 comparison of agricultural landscapes, 100 determining, 33 ecosystem variation, 42 effect of vegetation type, 48 field with shelterbelts, 77 forest, 77 landscape change effects, 50 landscape structure, 44 MBC model, 35 meadow, 77 seasonal values, landscape comparison, 101 Lead concentration in Turew, 175, 176 humic substances binding, 178 Leaf area index, 86 Lema melanopa, 198 Lepidoptera, in Turew, 202 Leptinotarsa decemlineata, 198 Lindane, Northern Parisian Basin surface water, 273–274 Linnet, utilizing field margins, 222 Lithuania, agricultural landscape protection, 305 Local hydrologic cycle, 58

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358

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Lombardian Lowland, afforestation, 304 Long-wave radiation, greenhouse gases, 31 Lumbricidae, See Earthworms

M Main River catchment, heat and water balance structure, 48 Mammals, in Turew, 202 Manure, See Fertilizer Marginal habitats as refuge habitats, 190 Mass flux, measuring, 33 Mass-energy exchange process, estimating, 32 Matrix, defined, 146 Matter cycling, 30 biogeochemical barriers, 301 human interference, 12 link to energy flux, 65 MBC model, 34 estimating heat balance components, 41 for long periods or large areas, 47 heat balance structure, 44, 52 latent and sensible heat flux, 35 Meadows, 98 ammonium cation concentrations, 121 animal body size, 196 animal diversity, 199 control of nitrogen pollution, 119–122 effect on metal speciation, 179 herbivore presence compared to wheat field, 198 humic substances binding toward heavy metals, 178 nitrogen processing, 124 plant diversity and native plants, 192 runoff, 87 width, 171–172, 173 Medisaprists, 115 Mediterranean region soil salinization, 16 water erosion, 14 Meles meles, in Turew shelterbelts, 208 Meligethes aeneus, 198 Metal ions, associated with humic substances, 177 Metals, See also Heavy metals chemical forms in Turew landscape, 176 in meadows, 179 speciation, 173, 174 toxicity, 174, 177 transport, 177 Microclimate biogeochemical barriers, 18 management, 344

relationship to land cover, 21 shelterbelt effects on, 98–99 Micro-water cycle, 58 Middle spotted woodpecker, in Turew shelterbelts, 208 Mid-field ponds, See also Biogeochemical barriers, Ponds humic substances flow control, 170 Miliaria calandra, in Turew shelterbelts, 208 Millponds, removal, 67, 255 Mineral fertilizers, 11 Minnesota (U.S.), dissolved organic matter concentrations, 164 Mites, agricultural effect on, 198 MODAM, See Land-use modeling, 286–294 Modeling, See also Land-use modeling environmental processes, 34 water balance structure, 30 Modular models, landscape modeling, 284 Moldova, agricultural landscape protection, 305 Monoculture, 332 Mosaic landscape, 5, See also Afforestations, Biogeochemical barriers, Field margins, Shelterbelts aboveground insect diversity, 203 biodiversity, 23, 185–211 biomass of aboveground insects, Romania, 203 bird species inhabiting Turew shelterbelts, 208 fertilizer application, 18 insect diversity, 202 landscape resistance, 98 mammals inhabiting Turew shelterbelts, 208 mean biomass of trophic groups, 203 modifying natural processes, 346 plant species richness, 190 precipitation, 86–87 predators, 203 refuge habitats for overwintering, 206 runoff, 87 water infiltration compared to nonmosaic, 99 water runoff, 74 weed diversity, 188 Müncheberg, Germany heat balance component measurements, 37 water balance structure studies, 76

N Natural succession, set-aside programs, 300 Nature protection, versus agriculture objectives, 341 Nebria brevicollis, in field margins, 234

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INDEX

Nematoda, 197 agriculture effect on, 198 in Turew, 202 Net radiation 32 comparison of agricultural landscapes, 100 ecosystem variation, 42 during growing season, Turew, 41 partitioning, 32, 43 Netherlands evapotranspiration/precipitation ratio, 60 ground water pollution, 16 nitrate concentrations, 112 Nitrates CAP Nitrates Directive, 343, 345 controlled by vegetation strips, 21 cultivated fields compared to drainage canals, 118 diffuse pollution, 112 high concentrations, Europe, 16 in watersheds, 160 nitrogen processing in biogeochemical barriers, 123 removal, plant uptake, 131 removal, riparian buffers, 150 runoff concentrations, Northern Parisian Basin, 273 shallow ground water, 113 Nitrates Directive (CAP), 343, 345 Nitrification tillage effects, 125 unfertilized plant cover, 129 Nitrogen control by biogeochemical barriers, 119–122, 131 control guidelines, 135 control through landscape management, 129–135 fertilizer relationship, 116–118 hapludalf soils, 134 internally recycled nitrogen pools, 138 nitrogen cycling regulation, 133 nitrogen uptake and water consumption, 130 nitrous oxide, 5, 127, 128, 129 plant litter, 134 role of transpiration, 132 shelterbelts network compared to patch, 133 Nitrogen cycling, 346 altered by agriculture, 334 internal recycling, 138 regulation, 133 Nitrogen leaching effect of precipitation, 121–122 plant litter decomposition, 133–134

359

Nitrogen processing ammonium cations in biogeochemical barriers,123 assimilatory nitrate reduction, 125 effect of tillage withdrawal, 125 fertilizer, 124 in biogeochemical barriers, 122–129 Nitrogen uptake, 5 periods of high water consumption, 130 wood compared to humus, 129 Nitrous oxide release, shelterbelts, 5, 127, 128, 129 Nonpoint pollution, See Diffuse pollution Northern Parisian Basin age of farms, 268 agricultural impact, 263–275 agro-industries, 267 biodiversity and pesticides, 274 contemporary crops, 264–265 crop yields, 266 described, 265 farm mechanization, 268 farm size, 266 fertilizer, 266, 272, 273, 275 floods, 269–271 fodder production, loss of, 268 loss of small fields, 268 map, 264 movement to agrarian capitalism, 272 open-field landscape, 268 potatoes, 268 soil erosion, 265, 268, 273 surface water with fertilizer and pesticides, 273 water erosion, 269 Note´c River, regulation in Wielkopolska region, 255 No-till agriculture, 332–333 water retention, 96 Nutrient dispersal, water runoff, 74 uptake, 346 replenishment, 11

O Oaks, afforestation, 307 Obra River, regulation in Wielkopolska region, 255 Odra River, regulation in Wielkopolska region, 255 Odonata, in Turew, 201 Open-field, 341 Northern Parisian Basin, 268–269 Organic matter decomposition, 5 decreased cycling, 4

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360

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

dissolved, 160 Ortolan bunting, in Turew shelterbelts, 208 Overwintering, 206 Oxidation, humic substances, 178

P Padova, Italy, field margin study, 223 Parisian Basin, See also Northern Parisian Basin shelterbelt decline, 306 Particulate organic carbon, 160, 161 Pastures, effect on riparian buffers, 152 Patch, defined, 146 Peatbog reclamation, effect on grasslands, 16 Pesticides, 11 agriculture leakiness, 147 biodiversity in Northern Parisian Basin, 274 impact on Northern Parisian Basin environment, 272 in surface water, Northern Parisian Basin, 273 in watersheds, 160 loading mitigation by riparian buffers, 149 reduced use at crop edge, 222 reducing input, 333 riparian buffers, 150 stabilization versus reduction, northern Parisian Basin, 275 Pests, See also Pesticides management, agrolandscape perspective, 333 monoculture, 332 PFRA, 303 Phosphates, absorption by biogeochemical barriers, 21 Phyloscopus sibilatrix, in Turew shelterbelts, 208 Physiotactics, 2 Phytoplankton, effect on polypeptide concentrations, 171 Picardy agriculture activity 263 farm size, 266 soil erosion, 273 Pied flycatcher, in Turew shelterbelts, 208 Plant cover, See also Landscape structure air and soil heating, 90 and weather, impact on evapotranspiration, 78–79 biogeochemical barriers, 301 buffering factor for water cycle, 77 controlling water balance structure, 98–101 diversification and weed diversity, 188 effect on precipitation, 71 effect on soil heat flux, 43

efficiency of energy utilization, 78–79 environmental resistance to degradation, 19 ground water recharge, 22 net radiation partitioning, 43 nitrogen pollution control, 132 root development and evapotranspiration, 88 simplification effects, 12, 195, 196 Plant cover, water relationship evaporation, 59 infiltration rates, 302 resource management, 21 retention, 96 runoff, 74 water balance structure, 58–102, 86–91 Plant disease, shelterbelts, 306 Plant diversity field margins, 234–239 for overall biodiversity, 210 native versus alien plants, 192 Poland, See also Turew, Wielkopolska region agricultural landscape protection, 305 climate and forestation change, 86, 102–103 crops and plant cover, 187 decreased shelterbelts, 306–307 evapotranspiration/precipitation ratio, 60 mean annual precipitation, 15 mid-field afforestation laws, 311 Prussian period, effect on forests, 321 transition to market economy, 258 water supply, 59, 60–61, 91 weed communities, 188 wooded areas, 321 Pollution, See Diffuse pollution Polypeptide concentrations in water, 170–171 Polysaccharide concentrations in water, 170–171 Ponds, 98, See also Biogeochemical barriers, Millponds water retention techniques, 97 Poplars, 308 Portugal, wetlands disappearance, 112 Potatoes Colorado beetles, 198 Northern Parisian Basin, 268 Potential water demand index (PWDI), 91 Precipitation, 70–72 comparison of agricultural landscapes, 100 effect of increased forestation, 86 effect of increased temperatures, 101–102 effect on humic substance concentrations, 165 effect on nitrogen leaching, 121–122 landscape structure, 71 runoff, 73 sensitivity to change, local versus regional scale, 86

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INDEX

361

variation, 65 Predators, 19, 203 Primula elation, 191 Protozoa, 197, 198 Pterostichus cupreus, in field margins, 233 PWDI, 91

R Radiation balance, 32 Rainfall, humic substance concentrations, 165 Rapeseed, Meligethes aeneus, 198 Raven, in Turew shelterbelts, 208 Reafforestations, See Afforestation Real water demand index (RWDI), 91 Recreational use of land, 259 Red-backed shrike, in Turew shelterbelts, 208 Reed bunting, utilizing field margins, 222 Refuge, 202, See also Animal communities afforestation, 300 mosaic landscape, 346 in Turew, 191 Regional approach, landscape modeling, 284 Regulating agriculture, enforcement, 343, 344 Remote sensing, See also Satellite imaging allocating ground data to satellite imagery, 329 choice of sampling unit, 324 density factor, 327 extraction by masking, 323 land unit samples, 323 measuring transitions, 325 overcoming disadvantages, 323 over-representation of land cover types, 325 reliability, 329 size and density of forest islets, 327 small-scale objects, 322 spatial resolution, 327 transect distribution, 328 forest islet density, 326 forest islets, 322 recording trajectory, 325 Rennes, France, field margin study, 223 Reptiles, in Turew, 202 Resource exploitation, feedback mechanisms, 3 Restoring wildlife, riparian buffers, 154, 155 Riparian buffers, 17, 98, 113, 148, 149 buffer widths, 155, 156 combined with conservation, 150 comparison of Georgia and Iowa implementations, 153 controlling environmental threats, 17 decision making, 153–156

decision tree, illustration, 154, 155 defined, 147 degraded riparian systems, 154 diffuse pollution control, 5, 131, 136, 148 distribution, 152 effect of pastures, 152 expanded definition, 148 fecal coliform, 152 forest buffers, 152 landscape management, 145–157 low dissolved oxygen, 152 managing, 151 nitrate control, 131 restoring wildlife, 154 scales of, 150 size, 150 sustaining, 150 time to establish function, 151 U.S. agriculture policy, 147 USDA programs, 151–153 water quality functions, 148, 149 wildlife, 154, 155 Riparian Ecosystem Management Model, 150 River regulation, effects of, 67 Wielkopolska region, 255 Rivers, organic matter content, 161 Roadsides, plant diversity (Turew), 192 Robninia pseudoacacia, 300 Roe deer, in Turew shelterbelts, 208 Romania aboveground insects, 200, 201, 203 soil salinization, 16 Rotational agriculture, traditional, 11 Row crops, runoff, 87 Runoff, 73–74 biogeochemical barriers, 301 mosaic landscape, 87 plant cover, 87, 302 row crops, 87 soil factors determining, 85 Turew, 120 Wielkopolska region, 255, 256 Runoff coefficient, 61 Rural areas, sustainable development, 278 Rural land use, sustainable development, 278–279 factors for success, 280 Rural settlement, 259 Russia aboveground insect populations, 200, 201 afforestation, 300 agricultural landscape protection, 305 Kursk, 27, 76 soil salinization, 16

0919 Index Frame Page 362 Wednesday, November 21, 2001 2:32 PM

362

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

water purification and afforestation, 302 RWDI, 91

S Satellite imaging, 322, See also Remote sensing matching with transect method, 325 Scolytidae, in Turew, 202 Scotch pine afforestation, 307 Sediment loading, mitigation by riparian buffers, 149 Semi-bocage, 300 Sensible heat flux climate zone differences, 77 determining, 33 landscape change effects, 50 MBS model, 35 seasonal variation in forests, 42 Set-aside programs, CAP, 300 Shelterbelts, 299, 300, 98, See also Afforestation, Biogeochemical barriers, Field margins, Riparian buffers age, 126, 128, 206 ammonium cation concentrations, 121 animal colonization, 205 animal diversity, 199 arid zones, 303 carbon dioxide, 127 Chlapowski recommendation, 300 classification 6 control of nitrogen pollution, 119–122 controlling environmental threats, 17 creating on fragmented estates, 305 crop protection, 310 diffuse pollution, in Turew, 113 effect on crop yields, 306 effect on micro-climate, 98–99 enconomic value, 311 heat balance structure components, illustrated, 46 lack of, 341 local resident attitudes, 309 managing heat balance structure, 43 mineral nitrogen in soil, 124 network, 133, 302 newly planted on endoaquolls, 125 nitrate control, 137, 138 nitrous oxide, 5, 127 on hapludalf soils, 124–126 phosphate and nitrate output from watersheds, 160 plant disease, 306 plant diversity, 192, 193

plant litter and nitrogen source, 134 plant species, 300 potential evapotranspiration reduction, 100 precipitation, 86 purification effects, 308 restricting cross pollination, 303 spatial arrangement, 310 supervision of, 311 Turew, 113, 115 water conservation, 39 water cycling, 22 water runoff, 74 width, 130, 131 windbreaking, 6, 308 Short-wave radiation, 31 Single crop farming, 332 Slash-and-burn agriculture, 11 Slope, biogeochemical barrier efficiency, 120 Slovak Republic, agricultural landscape protection, 305 Soil aeration, nitrification, 125 Soil compaction, 16 runoff, 87 Soil erosion conventional tillage, 332 cultivation practices, 265 northern Europe, 265 Northern Parisian Basin, 268 structure diversity, 18 Soil heat flux, 42 effect of plant cover, 43 plant cover effects on energy, 90 Soil moisture, 83, 84 dependence on texture, density, structure, 93 evapotranspiration, 90 Soil organic matter, 19 conserving as pollution control, 136 Soil, See also Bare soil ammonia sorption, 115 bare surface and evaporation, 84 conditions and water balance structure, 81 factors determining water conditions in, 85 fertility sustained naturally, 11 hydraulic conductivity (Turew and Wielkopolska light soils), 83 maximal water retention, 96 organic matter loss, 16 pF curve, 81, 82 plant cover and precipitation, 71 preventing water runoff, 74 quality, 344 salinization, 16 structure and available water, diagram, 83 structure, no-till agriculture, 332

0919 Index Frame Page 363 Wednesday, November 21, 2001 2:32 PM

INDEX

water available for plants, 82 water percolation, 115 water retention curves, 83 water flux, 83–85 water infiltration rate, 74 water storage, 17, 101 Soissonnais (France), farm size, 266 Solar energy flux, 29 biogeochemical barriers, 301 evapotranspiration intensity, 79 Solar energy partition, 4 Song thrush, utilizing field margins, 222 Spain evapotranspiration/precipitation ratio, 60 ground water pollution, 16 nitrate concentrations, 112 Zaragoza, 37, 76 Spatial approach, landscape modeling, 284 Spatial aspect modeling, 284–285 Spatial management, afforestation, 303 Spatial planning, 345 Species extinction and immigration, 319 Spiders agriculture effect on, 198 in Turew, 202 Spring crops, insect diversity, 202 Steppes, erosion, 302 Stepwise models, landscape modeling, 284 Stock farming, ties to crop, 257 Streams, organic matter content, 161 Subsurface water pathways, 116 Suburban villages, Wielkopolska region, 259 Sugar agriculture, 267 Sugar beet, evapotranspiration, 78 Surface water bound lead and copper concentrations, 177 chemistry of, 301 dissolved organic matter, 160, 163 humic substance concentrations, 165–170 Sus scrofa, in Turew shelterbelts, 208 Sustainable agriculture defined, 331 developing, 342 issues in, 331 rural land use, 23, 278–279 water quality, 111 Swidden farming, 254 Sycamore, afforestation, 307 Syrphidae, distribution correlation with aphids, 204 System sustainability, 21 Szwajcaria Zerkowska, plant species numbers, 190

363

T Techno-ecosystems, 336 Temperature increase, effect on crops, 101 Thematic approach, landscape modeling, 284 Three-field rotation, 11 Thysanoptera, in Turew, 199 Thysanoptera, Turew, 202 Tillage activity agriculture landscape leakiness, 147 alternatives to conventional, 322 animal abundance, 205 conventional, effects of, 332 withdrawal, effect on nitrogen processing, 125 Topsoil loss, 332 Transect sampling, 325 Transects distribution, using sattellite images, 328 orientation, 325 Transit water, 60, 61 Transpiration estimates, 130 nitrogen pollution control, 132 Trees, increasing evapotranspiration, 346 Tree sparrow, utilizing field margins, 222 Turbulence components, heat balance structure, 33 Turew, Poland ammonia volatilization, 127 animal community, 202 average latent heat flux, 100 average monthly precipitation, 69 biomass of aboveground insects, 200 breeding bird communities in afforestation, 207 dissolved organic matter concentrations, 162 drainage system and nitrogen concentrations, 116–119 earthworm distribution, 199 Enchytraeidae density and biomass, 200 evapotranspiration/precipitation ratio, 90 flying insect distribution, 201 ground water nitrates, 308 heat balance component measurements, 37 hydraulic conductivity of light soils, 83 land reclamation, 116 mean temperatures, 115 metal concentrations in water, 175 overview of agricultural landscape, 113–116 shelterbelt function studies, 113 shelterbelt width for pollution control, 131 surface water dissolved organic matter concentrations, 163 threatened weed species, 190, 191 Thysanoptera, 199

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364

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

vascular plants, 190, 192, 193 water balance structure studies, 76 water deficits, 115 water retention of light soils, 83 Turkey, beginning of agriculture, 10 Two-field system, 11

U Ukraine agricultural landscape protection, 305 soil salinization, 16 water erosion, 14 Uniform landscape, biological control of pests, 204 Urban landscape, agriculture landscape as buffer, 147 Urban systems, 336 Urban-industrial systems, 335 Urease activity analysis, 125 fluctuations, 126 USDA Conservation Buffer Initiative (CBI), 151 USDA Conservation Reserve Enhancement Program, 151–152 USDA Conservation Reserve Program (CRP), 151, 152

V Vegetation strips, See also Afforestations, Biogeochemical barriers, Field margins, Meadows, Riparian buffers, Shelterbelts Vertical energy flux, 23 Viola persicifolia, 191 Vistula River, afforestation, 305 Voivodeship, 250

W Wageningen, the Netherlands, field margin study, 223 Warta River, drought effects, 63 regulation in Wielkopolska region, 255 Water balance equation, 68 Water balance estimation, 35 Water balance structure agricultural landscape, 64–68 catchment, 68, 69 change as function of landscape structure, 44

climate conditions, 43, 70–72, 75–81, 100–104 climate zone differences, 76 comparison of agricultural landscapes, 99 component estimation, 34 controlling with plant cover, 97–100 dew and distillation, 86 evapotranspiration, 72–73 impact of landscape structure, table, 39 land use, 52, 86–91 landscape level, 59, 69 Main River catchment, 48 management, 58–102 modeling components, 30 overview, 60–64 plant cover, 59, 86–91 Poland, 15 precipitation, 70–72 runoff, 73–74 scale differences, 68 soil conditions, 81 water balance equation, 68 water fluxes, 68 wind effect, 98 Water conditions causes for worsening, 65 evaluating, 94 Water cycle, 30, See also Water balance structure biogeochemical barriers, 18 changes in, 59 climatic conditions, 6 diagram, 58 evapotranspiration, 22 landscape structure, 39, 71 management, 4 plant cover, 22, 77 relationship with energy flow, 91 scales of, 58 surface processes, 31 use of ponds, 97 Water deficits, 91–95 effect on biodiversity, 16 European Union, 14 Great Hungarian Plain, 61 Great Poland Plain, 61 in landscape, 91–96 Landscape Park im D. Chlapowskiego, 95 Poland, 15 storage versus retention, 96 Turew, 115 Wielkopolska region, 59 Water erosion, 13 Mediterranean region, 14 Ukraine, 14 Water flux, precipitation, 70–72

0919 Index Frame Page 365 Wednesday, November 21, 2001 2:32 PM

INDEX

Water management, 58–102 habitat moisture and landscape energy efficiency, 80 improving, 59, 95–97 landscape water deficits, 91–96 landscape, 91–100 mistakes in the past, 67 plant cover, 21 scale, 344 soil conditions, 81 water-energy relationsihip, 91, 92 Water phase transformation, 64 Water pollution control, 111 Water quality, 111 protection, 302 vegetation strips, 136 Water reservoirs, plant diversity and native plants, 192 Water retention biogeochemical barriers, 301 capacity, estimating, 97 improving, 59, 96–98 infiltration rate, 96 ponds, 97 ratio of water stored in pond and soil, 97–98 soil structure, 96 soil, 83 Water storage landscape, 18 target amounts, 94 Water functions in nature, 64 properties, 58 purification, 302 vapor flux, 69 Watershed contamination, 159–160 nitrate output, 131 nitrogen contamination, 334 Weather, See also Climate, Microclimate extreme, effect of afforestation, 303 plant cover impact on evapotranspiration, 78–79 water balance structure, 75–81 Weeds, 187, 188 field margins and hedgerows, 222 sown field margins, 241 threatened species, in Turew, 190 Wetlands, 98 as riparian zone, 148 draining, effects of, 67 eutrophication, 334 loss of, 15, 16, 112

365

Wheat fields energy for evapotranspiration compared to forests, 90 herbivore presence compared to meadow, 198 latent heat flux, 42 Wielkopolska region (Poland) 19th century land use, 254 afforestation, 254, 300 agricultural landscape development, 253–257 annual precipitation, 250 average monthly precipitation, 69–71 average temperatures, 250 changes in last millenium, 66 characteristics, 250 current agricultural characteristics, 257–259 dissolved organic matter concentrations, 161 drought risk, 61, 63 early human history and impact, 251–252 evapotranspiration, 60, 73, 101 family farms, 258 fauna changes, 256 fertilizer use, 255, 257–258 field characteristics, 258, 259 forest clearings, 253 forests, 250–251 homesteads converted to recreational use, 259 humic substances, 164–165 hydraulic conductivity of light soils, 83 hydrological parameters, 256 land-use changes, 253–257 metal speciation and meadow, 179 Mi¸edzychód, 255 natural landscape, 250–253 number of threatened plant species, 191 plant cover changes, 256 pond loss, 170 potential natural vegetation, 252 river regulation, 255 road network, 259 runoff, 255, 256 rural settlement, 259 sewage, 259 soil property changes, 256 surface water humic substance concentrations, 165 water balance, 64, 103 water resources, 59 water retention in light soils, 83 water runoff, 74 Zamorze, 256 Wildlife habitats afforestation, 304 field boundary, 220–232 Wildlife, conserving on farmland, 220

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366

LANDSCAPE ECOLOGY IN AGROECOSYSTEMS MANAGEMENT

Wind erosion, 13 water balance, 98 Windbreaks, 300 potential evapotranspiration reduction, 100 Winnowing machines, limiting weed diversity, 188 Winter crops, insect diversity, 202 Wood warbler, in Turew shelterbelts, 208 World water volume, 59

X Xenobiotics, agriculture leakiness, 147

Z Zamorze, 256 Zaragoza, heat balance component measurements, 37 Spain, water balance structure studies, 76 Zinc concentration, Turew, 175, 176 Zulawy (Poland), afforestation, 305